Abstracts (discont.)

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Bertram Koch, Robin Leblebici, Angel Martell, Sven Jörissen, Klaus Schilling, and Andreas Nüchter. Evaluating continuous-time SLAM using a predefined trajectory provided by a robotic arm. in Proceedings of the ISPRS Geospatial Week 2017, Laserscanning 2017, ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., Wuhan, China 2017, [Get Paper].

Abstract: Recently published approaches to SLAM algorithms process laser sensor measurements and output a map as a point cloud of the environment. Often the actual precision of the map remains unclear, since SLAM algorithms apply local improvements to the resulting map. Unfortunately, it is not trivial to compare the performance of SLAM algorithms objectively, especially without an accurate ground truth. This paper presents a novel benchmarking technique that allows to compare a precise map generated with an accurate ground truth trajectory to a map with a manipulated trajectory which was distorted by different forms of noise. The accurate ground truth is acquired by mounting a laser scanner on an industrial robotic arm. The robotic arm is moved on a predefined path while the position and orientation of the end-effector tool are monitored. During this process the 2D profile measurements of the laser scanner are recorded in six degrees of freedom and afterwards used to generate a precise point cloud of the test environment. For benchmarking, an offline continuous-time SLAM algorithm is subsequently applied to remove the inserted distortions. Finally, it is shown that the manipulated point cloud is reversible to its previous state and is slightly improved compared to the original version, since small errors that came into account by imprecise assumptions, sensor noise and calibration errors are removed as well.

Johannes Schauer and Andreas Nüchter. Digitizing automotive production lines without interrupting assembly operations through an automatic voxel-based removal of moving objects. in Proceedings of the 13th IEEE International Conference on Control and Automation (ICCA '17), Ohrid, Macedonia, July 2017. [Get Paper].
Also presented at the IEEE ICRA workshop on IC3 - Industry of the Future: Collaborative, Connected, Cognitive. Novel Approaches Stemming from Factory of the Future & Industry 4.0 Initiatives

Abstract: We present an efficient method to partition a point cloud gathered through kinematic laser scanning into static and dynamic points. The presented algorithm utilizes a voxel grid data structure and uses a ray intersection test to mark voxels as dynamic. The algorithm does not require any ego-motion estimations, computationally expensive object recognition or tracking of moving objects over time. It is easy to implement and can be executed on many cores in parallel. We show the viability of this approach by applying our algorithm to a dataset that we gathered by mounting a FARO Focus3D Laser scanner onto a skid which was then sent along a production line for consumer car chassis in a factory of the Volkswagen corporation. Since factory operators are interested in acquiring digital models of their production lines without suspending factory operations, the resulting point cloud will contain many dynamic objects like humans or other car bodies. We show how our algorithm is able to successfully remove these dynamic objects from the resulting point cloud with minimal errors. Our implementation is published under a free license as part of 3DTK.

Michael Bleier, André Dias, António Ferreira, John Pidgeon, José Miguel Almeida, Eduardo Silva, Klaus Schilling, and Andreas Nüchter. Signed Distance Function Based Surface Reconstruction of a Submerged Inland Mine Using Continuous-time SLAM. in Proceedings of the 20th World Congress of the International Federation of Automatic Control (WC '17), Toulouse, France, July 2017. [Get Paper].

Abstract: The planning of mining operations in water filled open-pit mines requires detailed bathymetry to create a mine plan and assess the involved risks. This paper presents post- processing techniques for creating an improved 3D model from a survey carried out using an autonomous surface vehicle with a multibeam sonar and a GPS/INS navigation system. Inconsistencies of the created point cloud as a result of calibration errors or GPS signal loss are corrected using a continuous-time simultaneous localization and mapping (SLAM) solution. Signed distance function based mapping is employed to fuse the measurements from multiple runs into a consistent representation and reduce sensor noise. From the signed distance function model we reconstruct a 3D surface mesh. We use this terrain model to establish a virtual reality scene for immersive data visualization of the mining operations for testing and planing during development. Results of the proposed approach are demonstrated on a dataset captured in an abandoned submerged inland mine.

Christian Pfitzner, Stefan May, and Andreas Nüchter. Evaluation of Features from RGB-D Data for Human Body Weight Estimation. in Proceedings of the 20th World Congress of the International Federation of Automatic Control (WC '17), Toulouse, France, July 2017. [Get Paper].

Abstract: Body weight is a crucial parameter when it comes to drug or radiation dosing. In case of emergency treatment time is short so that physicians estimate the body weight by the visual appearance of a patient. Further, visual body weight estimation might be a feature for person identification. This paper presents the anthropometric feature extraction from RGB-D sensor data, recorded from frontal view. The features are forwarded to an artificial neural network for weight estimation. Experiments with 233 people demonstrate the capability of different features for body weight estimation. To prove robustness against sensor modalities, a structured light sensor is used, as well as a time-of-flight sensor. An additional experiment including temperature features from a thermal camera improves the body weight estimation beyond.

Rainer Koch, Stefan May, and Andreas Nüchter. Effective Distinction Of Transparent And Specular Reflective Objects In Point Clouds Of A Multi-Echo Laser Scanner. in Proceedings of the 18th IEEE International Conference on Advanced Robotics (ICAR '17), Hongkong, July 2017. [Get Paper].

Abstract: A favoured sensor for mapping is a 3D laser scanner since it allows a wide scanning range, precise measurements, and is usable indoor and outdoor. Hence, a mapping module delivers detailed and high resolution maps which makes it possible to navigate safely. Difficulties result from transparent and specular reflective objects which cause erroneous and dubious measurements. At such objects, based on the incident angle, measurements result from the object surface, an object behind the transparent surface, or an object mirrored with respect to the reflective surface. This paper describes an enhanced Pre-Filter-Module to distinguish between these cases. Two experiments demonstrate the usability and show that for single scans the identification of mentioned objects in 3D is possible. The first experiment was made in an empty room with a mirror. The second experiment was made in a stairway which contains a glass door. Further, results show that a discrimination between a specular reflective and a transparent object is possible. Especially for transparent objects the detected size is restricted to the incident angle. That is why future work concentrates on implementing a post-filter module. Gained experience shows that collecting the data of multiple scans and postprocess them as soon as the object was bypassed will improve the map.

Rainer Koch, Lena Böttcher, Maximilian Jahrsdörfer, Johannes Maier, Malte Trommer, Stefan May, and Andreas Nüchter. Out of lab calibration of a rotating 2D Scanner for 3D mapping. in Proceedings of the SPIE optical metrology, Videometrics, Range Imaging, and Applications, Munich, Germany, June 2017. [Get Paper].

Abstract: Mapping is an essential task in mobile robotics. To fulfil advanced navigation and manipulation tasks a 3D~representation of the environment is required. Applying stereo cameras or Time-of-flight cameras (TOF cameras) are one way to archive this requirement. Unfortunately, they suffer from drawbacks which makes it difficult to map properly. Therefore, costly 3D laser scanners are applied. An inexpensive way to build a 3D representation is to use a 2D laser scanner and rotate the scan plane around an additional axis.
A 3D point cloud acquired with such a custom device consists of multiple 2D line scans. Therefore the scanner pose of each line scan need to be determined as well as parameters resulting from a calibration to generate a 3D point cloud. Using external sensor systems are a common method to determine these calibration parameters. This is costly and difficult when the robot needs to be calibrated outside the lab. Thus, this work presents a calibration method applied on a rotating 2D laser scanner. It uses a hardware setup to identify the required parameters for calibration. This hardware setup is light, small, and easy to transport. Hence, an out of lab calibration is possible. Additional a theoretical model was created to test the algorithm and analyse impact of the scanner accuracy.
The hardware components of the 3D scanner system are an HOKUYO UTM-30LX-EW 2D laser scanner, a Dynamixel servo-motor, and a control unit. The calibration system consists of an hemisphere. In the inner of the hemisphere a circular plate is mounted. The algorithm needs to be provided with a dataset of a single rotation from the laser scanner. To achieve a proper calibration result the scanner needs to be located in the middle of the hemisphere. By means of geometric formulas the algorithms determine the individual deviations of the placed laser scanner. In order to minimize errors, the algorithm solves the formulas in an iterative process.
First, the calibration algorithm was tested with an ideal hemisphere model created in Matlab. Second, laser scanner was mounted differently, the scanner position and the rotation axis was modified. In doing so, every deviation, was compared with the algorithm results. Several measurement settings were tested repeatedly with the 3D scanner system and the calibration system. The results show that the length accuracy of the laser scanner is most critical. It influences the required size of the hemisphere and the calibration accuracy.

Joachim Hertzberg, Kai Lingemann, and Andreas Nüchter. Mobile Roboter. Eine Einführung aus Sicht der Informatik. Springer, ISBN 978-3642017254, 2012. [Web page] [Springer page] [Get Book from Amazon]

Kurzbeschreibung: Mobile Roboter bewegen sich autonom im Raum. Die dafür notwendigen Berechnungen des Steuerungsprogramms beruhen wesentlich auf Sensordaten aus der Umgebung. Im Zentrum des Lehrbuchs stehen Algorithmen und Repräsentationen für die Steuerung mobiler Roboter. Aufbauend auf Kapiteln zu Sensorik und Sensordatenverarbeitung werden alle zentralen nicht-mechanischen Aspekte der Fortbewegung behandelt. Das erste Lehrbuch in deutscher Sprache zum Thema eignet sich nicht nur für das Bachelor-Studium, sondern auch zum Selbststudium und als Nachschlagewerk.
Buchrückseite: Wo bin ich? Wo soll ich hin? Wie komme ich dahin? Mobile Roboter in Alltagsumgebungen wie in Büros oder auf Straßen müssen ständig solche Fragen beantworten, sollen sie autonom, also ohne Fernsteuerung operieren. Die Berechnungen im Robotersteuerungsprogramm beruhen wesentlich auf Sensordaten aus der Umgebung, die oft unvollständig oder fehlerhaft sind. Das vorliegende Lehrbuch führt aus der Informatik-Perspektive in die entsprechenden Algorithmen und Repräsentationen ein. Ausgehend von Überblicken zu Sensorik und Sensordatenverarbeitung werden alle zentralen Aspekte der Steuerung autonomer mobiler Roboter behandelt: Bewegungsschätzung, Lokalisierung in Karten, Kartierung, Navigation, Umgebungsdateninterpretation und Software-Architekturen zur Robotersteuerung. Das Buch ist aus Lehrveranstaltungen entstanden und ist nicht nur für die Bachelor-Lehre an allen Hochschularten, sondern auch zum Selbststudium und als Nachschlagewerk geeignet.

Andreas Nüchter, Radu B. Rusu, Dirk Holz, and Daniel Munoz. Editorial: Semantic Perception, Mapping and Exploration. Journal of Robotics and Autonomous Systems (JRAS), Special Issue on Semantic Perception, Mapping and Exploration, Volume 62, Issue 5, May 2014. [Get Paper]

Semantic perception, mapping and exploration (SPME) for intelligent systems, such as robots, has seen a lot of progress recently, with many new and interesting techniques. When these intelligent systems are deployed in real-world environments, a variety of challenges are raised. For example, service robots need to plan in spaces exceeding their local perceptual space in order to cope with a wide variety of tasks, and robots operating in human living environments need to aggregate and model perceived semantic information. A further requirement for long-term autonomous operation is the ability to acquire and update the necessary information over time, which involves actively exploring the environment.

Andreas Nüchter. 3D Robotic Mapping. Springer Tracts in Advanced Robotics (STAR), ISBN 978-3540898832, 210 pages, Springer Verlag, 2009. [Springer Link] [Get Book].

About this book: The monograph written by Andreas Nüchter is focused on acquiring spatial models of physical environments through mobile robots. The robotic mapping problem is commonly referred to as SLAM (simultaneous localization and mapping). 3D maps are necessary to avoid collisions with complex obstacles and to self-localize in six degrees of freedom (x-, y-, z-position, roll, yaw and pitch angle). New solutions to the 6D SLAM problem for 3D laser scans are proposed and a wide variety of applications are presented.
Written for: Researchers, Graduate Students and Professionals in Robotics, Computer Vision and Multimedia

Andreas Nüchter. Semantische dreidimensionale Karten für autonome mobile Roboter, Dissertation (PhD thesis), University of Bonn, September 2006, also appeared as DISKI 303, ISBN 3-89838-303-2, Akademische Verlagsgesellschaft Aka GmbH, Berlin, Germany.

Zusammenfassung: Intelligentes autonomes Roboterhandeln in Alltagsumgebungen erfordert den Einsatz von 3D-Karten, in denen Objekte klassifiziert sind. 3D-Karten sind u.a. zur Steuerung notwendig, damit der Roboter komplexen Hindernissen ausweichen und sich mit 6 Freiheitsgraden (x-, y-, z-Position, Nick-, Gier-, und Rollwinkel) lokalisieren kann. Soll der Roboter mit seiner Umgebung interagieren, wird Interpretation unumgänglich. über erkannte Objekte kann der Roboter Schlussfolgerungen ziehen, sein Wissen wird inspizier- und kommunizierbar. Aus diesen Gründen ist die automatische und schnelle semantische 3D-Modellierung der Umgebung eine wichtige Fragestellung in der Robotik. 3D-Laserscanner sind eine junge Technologie, die die Erfassung räumlicher Daten revolutioniert und Robotern das dreidimensionale Abtasten von Objekten möglich macht. Die vorliegende Arbeit untersucht und evaluiert mit Hilfe eines 3D-Laserscanners und des mobilen Roboters Kurt3D die zur automatischen semantischen 3D-Kartenerstellung notwendigen Algorithmen.
Der erste Teil der Arbeit beschäftigt sich mit der Aufgabe, 3D-Scans in einem globalen Koordinatensystem zu registrieren. Korrekte, global konsistente Modelle entstehen durch einen 6D-SLAM Algorithmus. Hierbei werden 6 Freiheitsgrade in der Roboterpose berücksichtigt, geschlossene Kreise erkannt und der globale Fehler minimiert. Die Basis des 6D-SLAM ist ein sehr schneller ICP-Algorithmus. Im zweiten Teil geht es darum, die Punktmodelle mit Semantik zu versehen. Dazu werden 3D-Flächen in einer digitalisierten 3D-Szene detektiert und interpretiert. Anschliessend sucht ein effizienter Algorithmus nach Objekten und bestimmt deren Pose, ebenfalls mit 6 Freiheitsgraden. Schliesslich wird der in den zahlreichen Experimenten verwendete, mobile Roboter Kurt3D vorgestellt.

Abstract: Intelligent autonomous acting in unstructured environments requires 3D maps with labelled 3D objects. 3D maps are necessary to avoid collisions with complex obstacles and to self localize in six degrees of freedom (x-, y-, z-position, roll, yaw and pitch angle). Meaning becomes inevitable, if the robot has to interact with its environment. The robot is then able to reason about the objects; its knowledge becomes inspectable and communicable. These arguments lead to requiring automatic and fast semantic environment modelling in robotics. A revolutionary method for gaging environments are 3D scanners, which enable robots to scan objects in a non-contact way in three dimensions. The presented work examines and evaluates the algorithms needed for automatic semantic 3D map building using a 3D laser range finder and the mobile robot Kurt3D.
The first part deals with the task to register 3D scans in a common coordinate system. Correct, globally consistent models result from a 6D SLAM algorithm. Hereby 6 degrees of freedom of the robot pose are considered, closed-loops are detected and the global error is minimized. 6D SLAM is based on a very fast ICP algorithm. In the second part semantic descriptions are derived from the point model. For that purpose 3D planes are detected and interpreted in the digitalized 3D scene. After that an efficient algorithm detects objects and estimates their pose with 6 degrees of freedom, too. Finally, the mobile robot Kurt3D, that was used in numerous experiments is presented.

Andreas Nüchter, Kai Lingemann and Oliver Wulf (Eds.). Robotic 3D Environment Cognition, Workshop at the International Conference Spatial Cognition, Bremen, Germany 2006, [Get Workshop Proceedings (PDF)].

A fundamental problem in the design of autonomous mobile cognitive systems is the perception of the environment. Robotics researches this field in order to build reliable technical systems or to broaden the understanding of human perception. Perception is therefore studied independently by many researchers. On one hand, a basic part of the perception is to learn, detect and recognize objects, which has to be done with the limited resources of a mobile robot. The performance of a mobile system crucially depends on the accuracy, duration and reliability of its perceptions and the involved interpretation process. On the other hand, automatic environment sensing and modeling is a fundamental scientific issue in robotics, since the availability of maps is essential for many robot tasks.
A revolutionary method for gaging surroundings are 3D laser range finders and 3D cameras, which enable robots to quickly scan objects in a non-contact way in three dimensions. These emerging technologies have lead to new challenges and new potentials for data analysis. Firstly, robotic volumetric or 3D mapping of environments, considering all six degree of freedom of a mobile robot, has been done. Secondly, robots are able to perceive the geometry for avoiding collision in 3D and to identify and stay on navigable surfaces. In addition, 3D sensors have lead to new methods in object detection, object localization and identification.

Kurt Konolige and Andreas Nüchter. Range Sensors. in: Bruno Siciliano, Oussama Khatib (eds.): Springer Handbook of Robotics, 2nd ed., Chapter 31. Springer, 2016

Summary: Range sensors are devices that capture the 3D structure of the world from the viewpoint of the sensor, usually measuring the depth to the nearest surfaces. These measurements could be at a single point, across a scanning plane, or a full image with depth measurements at every point. The benefits of this range data is that a robot can be relatively certain where the real world is, relative to the sensor, thus allowing the robot to more reliably find navigable routes, avoid obstacles, grasp objects, act on industrial parts, etc.
This chapter introduces the main representations for range data (point sets, triangulated surfaces, voxels), the main methods for extracting usable features from the range data (planes, lines, triangulated surfaces), the main sensors for acquiring it (Section 31.1 - stereo and laser triangulation and ranging systems), how multiple observations of the scene, e.g. as if from a moving robot, can be registered (Section 31.3) and several indoor and outdoor robot applications where range data greatly simplifies the task (Section 31.4).

Joachim Hertzberg, Kai Lingemann, Christopher Lörken, Andreas Nüchter, and Stefan Stiene. Does it help a robot navigate to call navigability an affordance?. In Towards Affordance-Based Robot Control. Proceedings of Dagstuhl Seminar 06231, Dagstuhl Castle, Germany, June 5-9, 2006, Springer (LNAI vol. 4760), ISBN 978-3-540-77914-8, pp. 16-26, 2008. [Get Paper] [Springer Link]

Abstract: Gibson's notion of affordance seems to attract roboticists' attention. On a phenomenological level, it allows functions, which have "somehow" been implemented, to be described using a new terminology. However, that does not mean that the affordance notion is of help for building robots and their controllers. This paper explores viewing an affordance as an abstraction from a robot-environment relation that is of inter-individual use, but requires an individual implementation. Therefore, the notion of affordance helps share environment representations and theories among robots. Examples are given for navigability, as afforded by environments of different types to robots of different undercarriages and sensor configurations.

Long Chen, Lei Fan, Guodong Xie, Kai Huang, and Andreas Nüchter, Moving-Object Detection From Consecutive Stereo Pairs Using Slanted Plane Smoothing, in IEEE Transactions on Intelligent Transportation Systems , vol.PP, no.99, pp.1-10, 2017. doi: 10.1109/TITS.2017.2680538, [Get Paper].

Abstract: Detecting moving objects is of great importance for autonomous unmanned vehicle systems, and a challenging task especially in complex dynamic environments. This paper proposes a novel approach for the detection of moving objects and the estimation of their motion states using consecutive stereo image pairs on mobile platforms. First, we use a variant of the semi-global matching algorithm to compute initial disparity maps. Second, assisted by the initial disparities, boundaries in the image segmentation produced by simple linear iterative clustering are classified into coplanar, hinge, and occlusion. Moving points are obtained during ego-motion estimation by a modified random sample consensus) algorithm without resorting to time-consuming dense optical flow. Finally, the moving objects are extracted by merging superpixels according to the boundary types and their movements. The proposed method is accelerated on the GPU at 20 frames per second. The data which we use for testing and benchmarking is released, thus completing similar data sets. It includes 812 image pairs and 924 moving objects with ground truth for better algorithms evaluation. Experimental results demonstrate that the proposed method achieves competitive results in terms of moving-object detection and their motion state estimation in challenging urban scenarios.

Keith Y. K. Leung, Daniel Lühr, Hamidreza Houshiar, Felipe Inostroza, Dorit Borrmann, Martin Adams, Andreas Nüchter, and Javier Ruiz del Solar. El Teniente Underground Mine Dataset. International Journal of Robotics Research (IJRR), volume 36, issue 1, pages 16-23, January 2017, [Get Paper].

Abstract: This article presents a robotic dataset collected from El Teniente, the largest copper mine in the world. Sensor measurements from a 3D scanning lidar, a 2D radar, and stereo cameras were recorded from an approximately two kilometer traverse of a production-active tunnel. The equipment used and the data collection process are discussed in detail, along with the format of the data. This dataset is suitable for research in robotic navigation, as well as simultaneous localization and mapping (SLAM). Download instructions are available at the website http://dataset.amtc.cl.

Rainer Koch, Stefan May, Patrick Murmann, and Andreas Nüchter. Identification of Transparent and Specular Reflective Material in Laser Scans to Discriminate Affected Measurements for Faultless Robotic SLAM. Journal of Robotics and Autonomous Systems (JRAS), Elsevier Science, ISSN 0921-8890, Vol. 87, pages 296-312, 2017, [Get Paper].

Abstract: Mapping with laser scanners is the state-of-the-art method applied in service, industrial, medical, and rescue robotics. Although a lot of research has been done, maps still suffer from interferences caused by transparent and specular reflective objects. Glass, mirrors, shiny or translucent surfaces cause erroneous measurements depending on the incident angle of the laser beam. In past experiments the Mirror Detector Approach was implemented to determine such measurements with a multi-echo laser scanner. Recognition values are based on its differences in recorded measurements in regard to the distance of the echoes. This paper describes the research to distinguish between reflective and transparent objects. The implemented Mirror Detector was specifically modified for recognition of said objects for which four experiments were conducted; one experiment to show the map of the original Mirror Detector; two experiments to investigate intensity characteristics based on angle, distance, and material; and one experiment to show an applied discrimination with the extended version of the Mirror Detector, the Reflection Classifier Approach. To verify the results, a comparison with existing models was performed. This study showed that shiny metals, like aluminum, etc., provide significant characteristics, while mirrors are to be characterized by a mixed model of glass and shiny metal. Transparent objects turned out to be challenging because their appearance in the sensor data strongly depends on the background. Nevertheless, these experiments show that discrimination of transparent and reflective materials based on the reflected intensity is possible and feasible.

Ville V. Lehtola, Juho-Pekka Virtanen, Matti T. Vaaja, Hannu Hyyppä, and Andreas Nüchter. Localization of a Mobile Laser Scanner via Dimensional Reduction. Volume 121, pages 48-59,ISSN 0924-2716, Elsevier, ISPRS Journal of Photogrammetry and Remote Sensing (JPRS), November 2016.

Abstract: We extend the concept of intrinsic localization from a theoretical one-dimensional (1D) solution onto a 2D manifold that is embedded in a 3D space, and then recover the full six degrees of freedom for a mobile laser scanner with a simultaneous localization and mapping algorithm (SLAM). By intrinsic localization, we mean that no reference coordinate system, such as global navigation satellite system (GNSS), nor inertial measurement unit (IMU) are used. Experiments are conducted with a 2D laser scanner mounted on a rolling prototype platform, VILMA. The concept offers potential in being extendable to other wheeled platforms.

Philipp Koch, Stefan May, Michael Schmidpeter, Markus Kühn, Christian Pfitzner, Christian Merkl, Rainer Koch, Martin Fees, Jon Martin, and Andreas Nüchter. Multi-Robot Localization and Mapping based on Signed Distance Functions, Journal Intelligent Robot Systems, ISSN 0921-0296, Springer, Volume 83, Issue 3, pp. 409-428, September 2016, [Get Paper].

Abstract: This publication describes a 2D Simultaneous Localization and Mapping approach applicable to multiple mobile robots. The presented strategy uses data of 2D LIDAR sensors to build a dynamic representation based on Signed Distance Functions. Novelties of the approach are a joint map built in parallel instead of occasional merging of smaller maps and the limited drift localization which requires no loop closure detection. A multi-threaded software architecture performs registration and data integration in parallel allowing for drift-reduced pose estimation of multiple robots. Experiments are provided demonstrating the application with single and multiple robot mapping using simulated data, public accessible recorded data, two actual robots operating in a comparably large area as well as a deployment of these units at the Robocup rescue league.

Janusz Bedkowski Karol Majek, Piotr Majek, Pawel Musialik, Michal Pelka, and Andreas Nüchter. Intelligent Mobile System for Improving Spatial Design Support and Security Inside Buildings, Mobile Networks and Applications. Volume 20, Issue 6, pages 1-14; doi:10.1007/s11036-015-0654-8, ISSN 1383-469X, Springer, 2015. [Get Paper].

Abstract: This paper concerns an intelligent mobile application for spatial design support and security domain. Mobility has two aspects in our research: The first one is the usage of mobile robots for 3D mapping of urban areas and for performing some specific tasks. The second mobility aspect is related with a novel Software as a Ser- vice system that allows access to robotic functionalities and data over the Ethernet, thus we demonstrate the use of the novel NVIDIA GRID technology allowing to virtualize the graphic processing unit. We introduce Complex Shape Histogram, a core component of our artificial intelligence engine, used for classifying 3D point clouds with a Support Vector Machine. We use Complex Shape Histograms also for loop closing detection in the simultaneous localization and mapping algorithm. Our intelligent mobile system is built on top of the Qualitative Spatio-Temporal Representa- tion and Reasoning framework. This framework defines an ontology and a semantic model, which are used for building the intelligent mobile user interfaces. We show experiments demonstrating advantages of our approach. In addition, we test our prototypes in the field after the end-user case studies demonstrating a relevant contribution for future intelligent mobile systems that merge mobile robots with novel data centers.

Helge A. Lauterbach, Dorit Borrmann, Robin Heß, Daniel Eck, Klaus Schilling, and Andreas Nüchter. Evaluation of a Backpack-Mounted 3D Mobile Scanning System, Remote Sensing. 7(10), 13753-13781; doi:10.3390/rs71013753, 2015. [Get Paper].

Abstract: Recently, several backpack-mounted systems, also known as personal laser scanning systems, have been developed. They consist of laser scanners or cameras that are carried by a human operator to acquire measurements of the environment while walking. These systems were first designed to overcome the challenges of mapping indoor environments with doors and stairs. While the human operator inherently has the ability to open doors and to climb stairs, the flexible movements introduce irregularities of the trajectory to the system. To compete with other mapping systems, the accuracy of these systems has to be evaluated. In this paper, we present an extensive evaluation of our backpack mobile mapping system in indoor environments. It is shown that the system can deal with the normal human walking motion, but has problems with irregular jittering. Moreover, we demonstrate the applicability of the backpack in a suitable urban scenario.

Andreas Nüchter, Dorit Borrmann, Jan Elseberg, and David Redondo. A Backpack-Mounted 3D Mobile Scanning System. Allgemeine Vermessungs-Nachrichten (AVN), Volume 122, Issue 10, pages 301-307, ISSN 0002-5968, Wichmann Verlag, October 2015.

Abstract: Mobile laser scanning systems automate the acquisition of 3D point clouds of environments. The mapping systems are commonly mounted on cars or ships. This paper presents a mapping solution mounted on a backpack. A clever choice of hard- and software enables the system to generate 3D maps without using GPS (global positioning system) information and without relying on expensive IMU (inertial measurement unit) systems. Therefore, it enables flexible indoor mapping.
Mobile Laserscansysteme automatisieren die Aufnahme von 3D-Punktwolken zur Erfassung von Umgebungen. Die Kartierungssysteme werden üblicherweise auf Autos oder Schiffen montiert. In dieser Arbeit präsentieren wir eine Lsung, die sich auf einem Rucksack montieren lässt. Durch geschickte Auswahl von Hard- und Software kann das System 3D-Karten ohne GPS-Information und ohne teure inertiale Messsysteme erstellen. Daher ermglicht es flexibel Innenräume zu kartieren.

Johannes Schauer and Andreas Nüchter. Collision detection between point clouds using an efficient k-d tree implementation. Advanced Engineering Informatics, Elsevier, Volume 29, Issue 3, pages 440-458, August 2015. [Get Paper].

Abstract:
Context: An important task in civil engineering is the detection of collisions of a 3D model with an environment representation. Existing methods using the structure gauge provide an insufficient measure because the model either rotates or because the trajectory makes tight turns through narrow passages. This is the case in either automotive assembly lines or in narrow train tunnels.
Objective: Given two point clouds, one of the environment and one of a model and a trajectory with six degrees of freedom along which the model moves through the environment, find all colliding points of the environment with the model within a certain clearance radius.
Method: This paper presents two collision detection (CD) methods called kd-CD and kd-CD-simple and two penetration depth (PD) calculation methods called kd-PD and kd-PD-fast. All four methods are based on searches in a k-d tree representation of the environment. The creation of the k-d tree, its search methods and other features will be explained in the scope of their use to detect collisions and calculate depths of penetration.
Results: The algorithms are benchmarked by moving the point cloud of a train wagon with 2.5 million points along the point cloud of a 1144 meter long train track through a narrow tunnel with overall 18.92 million points. Points where the wagon collides with the tunnel wall are visually highlighted with their penetration depth. With a safety margin of 5 cm kd-PD-simple finds all colliding points on its trajectory which is sampled into 19392 positions in 77 seconds on a standard desktop machine of 1.6GHz.
Conclusion: The presented methods for collision detection and penetration depth calculation are shown to solve problems for which the structure gauge is an insufficient measure. The underlying k-d tree is shown to be an effective data structure for the required look-up operations.

Dorit Borrmann, Hamidreza Houshiar, Jan Elseberg, Andreas Nüchter, Falk Näth, Stephan Winkler. Das Framework Castle3D zur fortlaufenden semantischen 3D-Kartierung von archäologischen Ausgrabungsstätten. Allgemeine Vermessungs-Nachrichten (AVN), Wichmann Verlag, Volume 122, Issue 6-7, pages 233-246, 2015.

Abstract: Das 3D-Laserscanning ist Stand der Technik bei der Modellierung archäologischer Ausgrabungsstätten, historischer Anlagen und sogar ganzer Städte oder Landschaften. Die Dokumentation der Befunde auf einer Ausgrabungsstätte ist eine wesentliche archäologische Aufgabe. Ein automatisiertes System würde diesen Prozess beschleunigen und die Anzahl der Fehler auf ein Minimum reduzieren. Dieser Beitrag stellt einen neuen Ansatz in der Dokumentation industrieller Archäologie durch die Entwicklung einer standardisierten Herangehensweise an die computerunterstützte Dokumentation einer archäologischen Ausgrabungsstätte vor. Ausserdem wird eine Reihe von Tools zur Erfassung und Registrierung von 3D- Daten auf Ausgrabungsstätten vorgestellt, die den Hauptbestandteil der Arbeitskette abdecken. Ein effi­ zientes Werkzeug für die Visualisierung der erworbenen 3D-Punktwolken im 3D- und 2D-Modus wird zur Verfügung gestellt. Der Hauptzweck dieser Software ist es, Archäologen ein einfach zu bedienendes Tool für die semantische Kartierung vor Ort zu bieten. Es enthält Funktionen für die Auswahl und Kennzeich- nung von Funden. Jedes Label kann mit weiteren Informationen versehen werden. Diese Daten werden im XML-Format exportiert und dienen als Eingabe für andere Systeme und Datenbanken.

Mohammad Al-khawaldah and Andreas Nüchter. Enhanced frontier-based exploration for indoor environment with multiple robots, Advanced Robotics, Volume 29, Issue 10, pages 657-669, Taylor & Francis, ISSN 0169-1864, [Get Paper].

Abstract: In this paper, the exploration and map building of unknown environment by a team of mobile robots is intensively investigated. A new exploration technique is proposed to increase the exploration efficiency. In particular, the new technique has two main objectives: firstly, it aims at reducing the exploration time and the travelled distance by reducing the overlap which takes place when a certain area in the environment is explored by more than one robot. To achieve this, a new procedure to assign the next target location for each individual robot is proposed. And secondly, it aims at reducing computations complexity required by target selection and path planning tasks. More importantly, the proposed technique obviates the need for environment segmentation complex procedures which is adopted in some previous important research works. The new technique is intensively tested with different environments. The results showed the effectiveness of the proposed technique.

HamidReza Houshiar, Jan Elseberg, Dorit Borrmann, and Andreas Nüchter. A Study of Projections for Key Point Based Registration of Panoramic Terrestrial 3D Laser Scans, Journal of Geo-spatial Information Science, Volume 18, Issue 1, pages 11-31, Taylor & Francis, ISSN 1009-5020, [Get Paper].

Abstract: This paper surveys state of the art image features and descriptors for the task of 3D scan registration based on panoramic reflectance images. As modern terrestrial laser scanners digitize their environment in a spherical way, the sphere has to be projected to a two-dimensional image. To this end, we evaluate the equirectangular, the cylindrical, the Mercator, the rectilinear, the Pannini, the stereographic, and the z-axis projection. We show that the Mercator and the Pannini projection outperform the other projection methods.

Mohammad Al-khawaldah and Andreas Nüchter. Multi-Robot Cooperation for Efficient Exploration. Automatika - Journal for Control, Measurement, Electronics, Computing and Communications, ISSN 0005-1144, Volume 55, No 3, pages 276-286, 2014, [Get Paper]. [Get Paper].

Abstract: This paper addresses the problem of exploration of an unknown environment by developing effective exploration strategies for a team of mobile robots equipped with continuously rotating 3D scanner. The main aim of the new strategies is to reduce the exploration time of unknown environment. Unlike most of other published works, to save time, the laser scanners rotate and scan the environment while robots are in motion. Furthermore, the new strategies are able to explore large outdoor environments as a considerable reduction of the required computations, especially those required for path planning, have been achieved. Moreover, a new exploration strategy has been developed so that robots continuously replan the order to visit the remaining unexplored areas according to the new data (i.e. updated map) collected by the robot in question or by the other team members. The new extension led to further enhancement but with slightly higher computational costs. Finally, to assess our new exploration strategies with different levels of environment complexity, new set of experiments were conducted in environments where obstacles are distributed according to the Hilbert curve. The results of these experiments show the effectiveness of the proposed technique to effectively distribute the robots over the environment. More importantly we show how the optimal number of robots is related to the environment complexity.

Girum Demisse, Dorit Borrmann, and Andreas Nüchter. Interpreting Thermal 3D Models of Indoor Environments for Energy Efficiency. In Journal of Intelligent and Robotic Systems, Springer, ISSN 0921-0296, Volume 77, Issue 1, pages 55-72, January 2015, [Get Paper].

Abstract: In recent years 3D models of buildings are used in maintenance and inspection, preservation, and other building related applications. However, the usage of these models is limited because most models are pure representations with no or little associated semantics. In this paper we present a pipeline of techniques used for interior interpretation, object detection, and adding energy related semantics to windows of a 3D thermal model. A sequence of algorithms is presented for building the fundamental semantics of a 3D model. Among other things, these algorithms enable the system to differentiate between objects in a room and objects that are part of the room, e.g. floor, windows. Subsequently, the thermal information is used to construct a stochastic mathematical model - namely Markov Random Field - of the temperature distribution of the detected windows. As a result, the MAP (Maximum a posteriori) framework is used to further label the windows as either open, closed or damaged based upon their temperature distribution. The experimental results showed the robustness of the techniques. Furthermore, a strategy to optimize the free parameters is described, in cases where there is a sample training dataset.

Dorit Borrmann, Andreas Nüchter, Marija Dakulovic, Ivan Maurovic, Ivan Petrovic, Dinko Osmankovic, and Jasmin Velagic. A mobile robot based system for fully automated thermal 3D mapping. Advanced Engineering Informatics, Elsevier, ISSN 1474-0346, Volume 28, Issue 4, pages 425–440, October 2014, [Get paper].

Abstract: It is hard to imagine living in a building without electricity and a heating or cooling system these days. Factories and data centers are equally dependent on a continuous functioning of these systems. As beneficial as this development is for our daily life, the consequences of a failure are critical. Malfunctioning power supplies or temperature regulation systems can cause the close-down of an entire factory or data center. Heat and air conditioning losses in buildings lead to a large waste of the limited energy resources and pollute the environment unnecessarily. To detect these flaws as quickly as possible and to prevent the negative consequences constant monitoring of power lines and heat sources is necessary. To this end, we propose a fully automatic system that creates 3D thermal models of indoor environments.
The proposed system consists of a mobile platform that is equipped with a 3D laser scanner, an RGB camera and a thermal camera. A novel 3D exploration algorithm ensures efficient data collection that covers the entire scene. The data from all sensors collected at different positions is joined into one common reference frame using calibration and scan matching. In the post-processing step a model is built and points of interest are automatically detected. A viewer is presented that aids experts in analyzing the heat flow and localizing and identifying heat leaks. Results are shown that demonstrate the functionality of the system.

Qingquan Li, Long Chen, Ming Li, Shih-Lung Shaw, and Andreas Nüchter. A Sensor-Fusion Drivable-Region and Lane-Detection System for Autonomous Vehicle Navigation in Challenging Road Scenarios. IEEE Transactions on vehicular technology, 62(2):540-555, February 2014. [Get Paper]

Abstract: Autonomous vehicle navigation is challenging since various types of road scenarios in real urban environments have to be considered, especially when only perception sensors are used, without position information. This paper presents a novel real-time optimal-drivable-region and lane detection system for autonomous driving based on the fusion of Light Detection and Ranging (LIDAR) and vision data. Our system uses a multisensory scheme to cover the most drivable areas in front of the vehicle. We propose a feature-level fusion method for LIDAR and vision data and an optimal selection strategy for detection of the best drivable region. Then a conditional lane detection algorithm is selectively executed depending on an automatic classification of the optimal drivable region. Our system successfully handles both structured and unstructured roads. The results of several experiments are provided to demonstrate the reliability, effectiveness, and robustness of the system.

Jan Elseberg, Dorit Borrmann, and Andreas Nüchter. Algorithmic Solutions for Computing Precise Maximum Likelihood 3D Point Clouds from Mobile Laser Scanning Platforms, Remote Sensing. 5(11), 5871-5906; doi:10.3390/rs5115871, 2013. [Get Paper].

Abstract: Motivated by Mobile laser scanning puts high requirements on the accuracy of the positioning systems and the calibration of the measurement system. We present a novel algorithmic approach for calibration with the goal of improving the measurement accuracy of mobile laser scanners. We describe a general framework for calibrating mobile sensor platforms that estimates all configuration parameters for any arrangement of positioning sensors including odometry. In addition, we present a novel semi-rigid Simultaneous Localization and Mapping (SLAM) algorithm that corrects the vehicle position at every point in time along its trajectory, while simultaneously improving the quality and precision of the entire acquired point cloud. Using this algorithm the temporary failure of accurate external positioning systems or the lack thereof can be compensated for. We demonstrate the capabilities of the two newly proposed algorithms on a wide variety of data sets.

Andreas Nüchter, Jan Elseberg, and Dorit Borrmann. Automation in 3D Laser Scanning -- From an Automated Tripod towards Optimal 3D Point Clouds from Mobile Laser Scanning. GIM International, Volume 27, Number 9, September 2013, [Get Paper].

Abstract: Motivated by the increasing need of rapid characterization of environments in 3D, we designed a robot system that automates the work of an operator of terrestrial laser scanners. The built system enables to work without markers or targets and enables the surveyors to save more than 75% of the time spent in the field. Another impulse for developing the platform is the demand for a remote inspection tool. The robot is capable to survey remote sites or danger areas, such as plants, underground mines, tunnels and caves, or channels. The availability of the robotic platform further enables us to study mobile laser scan systems. Now, the system is ready to do the work.
This article details the mobile robot, before we present our software solution. The software consists of automatic, high-precise registration programs for terrestrial scans, i.e., bundle adjustment, and its extension to mobile mapping, which requires precise calibration and trajectory optimization. Our algorithms do not rely on features at any point.

Janusz Bedkowski, Karol Majek, and Andreas Nüchter. General Purpose Computing on Graphics Processing Units for Robotic Applications. Journal of Software Engineering for Robotics (JOSER), Volume 4, Number 1, pages 23-33, ISSN 2035-3928, 2013. [Get Paper (PDF)].

Abstract: This paper deals with research related with the improvements of state of the art algorithms used in robotic applications based on parallel computation. The main goal is to decrease the computational complexity of 3D cloud of points processing in such applications as: data filtering, normal vector estimation, data registration and calculation of point feature histogram. The presented results efficiently improve the existing implementations with minimal lost of accuracy. The main contribution is a regular grid decomposition originally implemented for nearest neighborhood search. This data structure is used almost for all presented methods, it provides an efficient method for decreasing the time of computation. The results are compared with well-known robotic frameworks such as PCL and 3DTK.

Jan Elseberg, Dorit Borrmann, Andreas Nüchter. One Billion Points in the Cloud - An Octree for Efficient Processing of 3D Laser Scans, ISPRS Journal of Photogrammetry & Remote Sensing (JPRS), Special issue on terrestrial 3D modelling, Elsevier Science, Volume 76, pp. 76-88, ISSN 0924-2716, February 2013 [Get Paper].

Abstract: Automated 3-dimensional modeling pipelines include 3D scanning, registration, data abstraction, and visualization. All steps in such a pipeline require the processing of a massive amount of 3D data, due to the ability of current 3D scanners to sample environments with a high density. The increasing sampling rates make it easy to acquire Billions of spatial data points. This paper presents algorithms and data structures for handling these data. We propose an efficient octree to store and compress 3D data without loss of precision. We demonstrate its usage for an exchange file format, fast point cloud visualization, sped-up 3D scan matching, and shape detection algorithms. We evaluate our approach using typical terrestrial laser scans.

Jan Elseberg, Stéphane Magnenat, Roland Siegwart, and Andreas Nüchter. Comparison of nearest-neighbor-search strategies and implementations for efficient shape registration. Journal of Software Engineering for Robotics (JOSER), Volume 3, Number 1, ISSN 2035-3928, pages 2-12, 2012. [Get Paper (PDF)].

Abstract: The iterative closest point (icp) algorithm is one of the most popular approaches to shape registration currently in use. At the core of icp is the computationally-intensive determination of nearest neighbors (NN). As of now there has been no comprehensive analysis of competing search strategies for NN. This paper compares several libraries for nearest-neighbor search (NNS) on both simulated and real data with a focus on shape registration. In addition, we present a novel efficient implementation of NNS via k-d trees as well as a novel algorithm for NNS in octrees.

Jan Elseberg, Dorit Borrmann, and Andreas Nüchter. Eine Milliarde 3D-Punkte mit Standardhardware verarbeiten – Processing One Billion 3D Points on a Standard Computer. Allgemeine Vermessungs-Nachrichten (AVN), AVN-Themenheft mit Beiträgen aus den 3D-Tagen Oldenburg 2011, pages 11 - 23, Volume 119, Number 1, January 2012.

Abstract: Dieser Beitrag stellt eine neue Implementation der Octree-Datenstruktur vor. Sie ermöglicht es, eine Milliarde 3D-Punkte in 8 GB Hauptspeicher exakt zu repräsentieren und effiziente Algorithmen zu implementieren. Der Octree gibt eine Hierarchie vor, die dazu verwendet werden kann, grosse Punktwolken zu inspizieren und flüssig in ihnen zu navigieren. Des Weiteren schlagen wir in diesem Artikel ein effizentes binäres Dateiformat für den Austausch von 3D-Scans vor.
Schlüsselbegriffe: 3D-Punktwolke, Octree, Baumartige Datenstrukturen, verlustfreie Datenkomprimierung

In this paper we describe a new implementation of the spatial data structure called octree. We present an encoding that is capable of storing one billion points in 8 GB memory. The octree imposes a hierachy that can be used to inspect and visualize large point clouds and to navigate smoothly in it. In addition, we propose an efficient file format for exchanging 3D scans.
Key words: 3D point cloud, octree, tree like data structures, lossless compression, file formats

Jochen Sprickerhof, Andreas Nüchter, Kai Lingemann, and Joachim Hertzberg. A Heuristic Loop Closing Technique for Large-Scale 6D SLAM. Automatika - Journal for Control, Measurement, Electronics, Computing and Communications, Special Issue with selected papers from the European Conference on Mobile Robots 2009, Volume 52, Number 3, 2011. [Get Paper (PDF)].

Abstract: This paper presents a novel heuristic for correcting scan pose estimations after loop closing in SLAM using 3D laser scans. Contrary to state of the art approaches, the built SLAM graph is sparse, and optimization is done without any iteration between the SLAM front and back end, yielding a highly efficient loop closing method.
Several experiments were carried out in an urban environment and evaluated against ground truth. The results are compared to other state of the art algorithms, proving the high quality, yet achieved faster by an order of magnitude.

Andreas Nüchter, Stanislav Gutev, Dorit Borrmann, and Jan Elseberg. Skyline-based Registration of 3D Laser Scans. Journal of Geo-spatial Information Science, Special Issue with selected papers from the 3D City Modeling and Applications Workshop. Volume 14, Number 2, pages 85-90, ISSN 1009-5020, Springer Verlag, June 2011, [Get Paper] [Springer Link].

Abstract: Acquisition and registration of terrestrial 3D laser scans is a fundamental task in mapping and modeling of cities in three dimensions. To automate this task marker-free registration methods are required. Based on the existence of skyline features this paper proposes a novel method. The skyline features are extracted from panoramic 3D scans and encoded as strings enabling the use of string matching for merging the scans. Initial results of the proposed method in the old city center of Bremen are presented.

Dorit Borrmann, Jan Elseberg, Kai Lingemann, and Andreas Nüchter. The 3D Hough Transform for Plane Detection in Point Clouds - A Review and A new Accumulator Design, Journal 3D Research, ISSN 2092-6731, Springer, Volume 2, Number 2, March 2011, [Get Paper (PDF)] [Springer Link].

Abstract: The Hough Transform is a well-known method for detecting para\-metrized objects. It is the de facto standard for detecting lines and circles in 2-dimensional data sets. For 3D it has attained little attention so far. Even for the 2D case high computational costs have lead to the development of numerous variations for the Hough Transform. In this article we evaluate different variants of the Hough Transform with respect to their applicability to detect planes in 3D point clouds reliably. Apart from computational costs, the main problem is the representation of the accumulator. Usual implementations favor geometrical objects with certain parameters due to uneven sampling of the parameter space. We present a novel approach to design the accumulator focusing on achieving the same size for each cell and compare it to existing designs.

Stanislav Serebryakov, Lev Stankewich, and Andreas Nüchter. Визуальная навигация с времяпролетной камерой (Visual SLAM with Time-of-Flight Camera). Научно-технический ОПТИЧЕСКИЙ ЖУРНАЛ (Journal of Optical Technology). Volume 77, Issue 10, ISSN 0030-4042, pages 51-55, November 2010,

Abstract: В статье представлена система визуальной навигации в реальном времени с использованием времяпролетной камеры без априорных знаний о сцене. Представлен спо соб комплексирования времяпролетной и оптической камеры. Рассмотрены методы повышения робастности локализации, учитывающие цветовую и пространственную информацию.
The article presents a visual navigation system in real time using the time-of-flight camera without a priori knowledge of the scene. A method for fusing time-of- flight and the optical camera and methods for increasing the robustness of localization, taking into account the color and spatial information is discussed.

Joachim Hertzberg, Kai Lingemann, Christopher Lörken, Andreas Nüchter, Stefan Stiene and Thomas Wiemann. 3D-Roboterkartenbau in Osnabrück, KI Künstliche Intelligenz: Themenschwerpunk Simultaneous Localization and Mapping (SLAM) Volume 24, Number 3, September 2010 [Get Paper (PDF)].

Zusammenfassung: Seit Herbst 2004 existiert die Arbeitsgruppe "Wissensbasierte Systeme" am Institut für Informatik der Universität Osnabrück. Eines ihrer Arbeitsthemen ist der Bau von Roboterkarten basierend auf 3D-Laserscans bei 6-dimensionalen Scanposen. Wir geben einen Überblick über die wichtigsten Ergebnisse dazu und über die Perspektive dieses Themas für die Zukunft.

Andreas Nüchter, Jan Elseberg, Peter Schneider, and Dietrich Paulus. Study of Parameterizations for the Rigid Body Transformations of The Scan Registration Problem, Journal Computer Vision and Image Understanding (CVIU), Elsevier Science, Volume 114, Issue 8, pp. 963-980, ISSN 1077-3142, August 2010. [Get Paper (PDF)] [Elsevier Link with supplementary content].

Abstract: The ICP (Iterative Closest Point) algorithm is the de facto standard for geometric alignment of three-dimensional models when an initial relative pose estimate is available. The basis of the algorithm is the minimization of an error function that takes point correspondences into account. Four closed-form solution methods are known for minimizing this function. This paper presents novel linear solutions to the scan registration problem, i.e., to the problem of putting and aligning 3D scans in a common coordinate system. We extend the methods for registering n-scans in a global and simultaneous fashion, such that the registration of the n-th scan influences all previous registrations in one step.

Martin Magnusson, Henrik Andreasson, Andreas Nüchter, and Achim J. Lilienthal. Automatic Appearance-Based Loop Detection from 3D Laser Data Using the Normal Distributions Transform, Journal of Field Robotics (JFR), Special Issue on Three-Dimensional Mapping, Volume 26, Issue 11-12, November - December, 2009 [Get Paper (PDF)].

Abstract: We propose a new approach to appearance-based loop detection for mobile robots, using 3D laser scans. Loop detection is an important problem in the SLAMdomain, and, because it can be seen as the problem of recognizing previously visited places, it is an example of the data association problem. Without a flat floor assumption, 2D laser-based approaches are bound to fail in many cases. Two of the problems with 3D approaches that we address in this paper are how to handle the greatly increased amount of data and how to efficiently obtain invariance to 3D rotations. We present a compact representation of 3D point clouds that is still discriminative enough to detect loop closures without false positives (i.e., detecting loop closure where there is none). A low false positive rate is very important because wrong data association could have disastrous consequences in a SLAM algorithm. Our approach uses only the appearance of 3D point clouds to detect loops and requires no pose information. We exploit the NDT surface representation to create feature histograms based on surface orientation and smoothness. The surface shape histograms compress the input data by two to three orders of magnitude. Because of the high compression rate, the histograms can be matched efficiently to compare the appearance of two scans. Rotation invariance is achieved by aligning scans with respect to dominant surface orientations. We also propose to use expectation maximization to fit a Gamma mixture model to the output similarity measures in order to automatically determine the threshold that separates scans at loop closures from non-overlapping ones. We discuss the problem of determining ground truth in the context of loop detection and the difficulties in comparing the results of the few available methods based on range information. Furthermore, we present quantitative performance evaluations using three real-world data sets, one of which is highly self-similar, showing that the proposed method achieves high recall rates (percentage of correctly identified loop closures) at low false positive rates in environments with different characteristics.

Stefan May, David Dröschel, Dirk Holz, Stefan Fuchs, Ezio Malis, Andreas Nüchter, and Joachim Hertzberg. 3D Mapping with Time-of-Flight Cameras. Journal of Field Robotics (JFR), Special Issue on Three-Dimensional Mapping, Volume 26, Issue 11-12, November - December, 2009 [Get Paper (PDF)].

Abstract: This article investigates the use of Time-of-Flight (ToF) cameras in mapping tasks for autonomous mobile robots, in particular in simultaneous localization and mapping (SLAM) tasks. While ToF cameras are in principle an attractive type of sensor for 3D mapping owing to their high rate of frames of 3D data, two features of them make them difficult as mapping sensors, namely, their restricted field of view and influences on the quality of range measurements by high dynamics in object reflectivity; in addition, currently available models suffer from poor data quality in a number of aspects. The paper first summarizes calibration and filtering approaches for improving accuracy, precision and robustness of ToF camera independent of their intended usage. Then, several ego motion estimation approaches are applied or adapted, respectively, in order to provide a performance benchmark for registering ToF camera data. As a part of this, an extension to the Iterative Closest Point (ICP) algorithm has been developed that increases the robustness under restricted field of view and under larger displacements. Using an indoor environment, the paper provides results from SLAM experiments using these approaches in comparison. It turns out that the application of ToF cameras is feasible to SLAM tasks, although this type of sensor has a complex error characteristic.

Simone Frintrop, Andreas Nüchter, Kai Pervölz, Hartmut Surmann, Sara Mitri, Joachim Hertzberg. Attentive Classification, International Journal of Applied Artificial Intelligence in Engineering Systems, ISSN 0975-3176, Vol. 1, Number 1, June 2009. [Get Paper (PDF)]

Abstract: In this paper, we present a two-step approach for object recognition based on principles of human perception: Attentive Classification. First, regions of interest are detected by a biologically motivated attention system. Second, these regions are analyzed by a fast classifier based on the Adaboost learning technique. Thus, the classification effort is restricted to a small data subset. The approach has two advantages over normal classification: First, the system becomes considerably faster, which is an important factor for real-time systems. Second, since the attention system is able to make use of top-down target-information, the combination of the systems yields a significant reduction of false detections for objects which are usually difficult to discriminate from the surrounding. We show the performance of the system in several experiments in robotic scenarios. The presented attentive classification system represents an important step towards effective general object recognition which is fast, robust and flexibly adaptable to a current task.

Andreas Nüchter. Parallel and Cached Scan Matching for Robotic 3D Mapping. Journal of Computing and Information Technology Processing (eCIT), Special Issue on Advanced Mobile Robotics, Volume 17, Number 1, ISSN 1330-1136, pages 51-65, March 2009 [Get Paper (PDF)] [eCIT site].

Abstract: Intelligent autonomous acting of mobile robots in unstructured environments requires 3D maps. Since manual mapping is a tedious job, automatization of this job is necessary. Automatic, consistent volumetric modeling of environments requires a solution to the simultaneous localization and map building problem (SLAM problem). In 3D this task is computationally expensive, since the environments are sampled with many data points with state of the art sensing technology. In addition, the solution space grows exponentially with the additional degrees of freedom needed to represent the robot pose. Mapping environments in 3D must regard six degrees of freedom to characterize the robot pose. This paper summarizes our 6D SLAM algorithm and presents novel algorithmic and technical means to reduce computation time, i.e., the data structure cached k-d tree and parallelization. The availability of multi-core processors as well as efficient programming schemes as OpenMP permit the parallel execution of robotics tasks.

Andreas Nüchter and Joachim Hertzberg. Towards Semantic Maps for Mobile Robots. Journal of Robotics and Autonomous Systems (JRAS), Special Issue on Semantic Knowledge in Robotics, Elsevier Science, Volume 56, Issue 11, ISSN 0921-8890, pages 915-926, 2008. [ScienceDirect Link] [Get Paper].

Abstract: Intelligent autonomous action in ordinary environments calls for 3D maps. 3D geometry is necessary for avoiding collision with complex obstacles and to self localize in six degrees of freedom (6 DoF) (x, y, z positions, roll, yaw, and pitch angles). Meaning, in addition to geometry, becomes inevitable if the robot is supposed to interact with its environment in a goal-directed way. A semantic stance enables the robot to reason about objects; it helps disambiguate or round off sensor data; and the robot knowledge becomes reviewable and communicable.
The paper describes an approach and a completed robot system for semantic mapping. The prime sensor is a 3D laser scanner. Individual scans are registered into a coherent 3D geometry map by 6D SLAM. Coarse scene features (e.g., walls, floors in a building) are determined by semantic labeling. More delicate objects are then detected by a trained classifier and localized. In the end, the semantic maps can be visualized for human inspection. We sketch the overall architecture of the approach, explain the respective steps and their underlying algorithms, give examples based on a working robot implementation, and discuss the findings.

Oliver Wulf, Andreas Nüchter, Joachim Hertzberg, and Bernardo Wagner. Benchmarking Urban Six-Degree-of-Freedom Simultaneous Localization and Mapping. Journal of Field Robotics (JFR), Wiley & Son, ISSN 1556-4959, Vol. 25, Issue 3, pages 148 - 163, March, 2008, [Get Paper] [Get Videos].

Abstract: Quite a number of approaches for solving the simultaneous localization and mapping (SLAM) problem exist by now. Some of them have recently been extended to mapping environments with six degrees of freedom (DoF) poses, yielding 6D SLAM approaches. To demonstrate the capabilities of the respective algorithms, it is common practice to present generated maps and successful loop closings in large outdoor environments. Unfortunately, it is non-trivial to compare different 6D SLAM approaches objectively, because ground truth data about the outdoor environments used for demonstration is typically unavailable. We present a novel benchmarking method for generating this ground truth data based on reference maps. The method is then demonstrated by comparing the absolute performance of some previously existing 6D SLAM algorithms which build a large urban outdoor map.

Dorit Borrmann, Jan Elseberg, Kai Lingemann, Andreas Nüchter and Joachim Hertzberg. Globally consistent 3D mapping with scan matching. Journal of Robotics and Autonomous Systems (JRAS), Elsevier Science, Vol. 56, Issue 2, ISSN 0921-8890, pages 130 - 142, February 2008, [ScienceDirect Link] [Get Paper] [Get Videos] [Addendum].

Abstract: A globally consistent solution to the simultaneous localization and mapping (SLAM) problem in 2D with three degrees of freedom (DoF) poses was presented by Lu and Milios [F. Lu, E. Milios, Globally consistent range scan alignment for environment mapping, Autonomous Robots 4 (April) (1997) 333-349]. To create maps suitable for natural environments it is however necessary to consider the 6DoF pose case, namely the three Cartesian coordinates and the roll, pitch and yaw angles. This article describes the extension of the proposed algorithm to deal with these additional DoFs and the resulting non-linearities. Simplifications using Taylor expansion and Cholesky decomposition yield a fast application that handles the massive amount of 3D data and the computational requirements due to the 6DoF. Our experiments demonstrate the functionality of estimating the exact poses and their covariances in all 6DoF, leading to a globally consistent map. The correspondences between scans are found automatically by use of a simple distance heuristic.

Andreas Nüchter, Kai Lingemann, Joachim Hertzberg, and Hartmut Surmann, 6D SLAM - 3D Mapping Outdoor Environments Journal of Field Robotics (JFR), Special Issue on Quantitative Performance Evaluation of Robotic and Intelligent Systems, Wiley & Son, ISSN 1556-4959, Vol. 24, Issue 8-9, pages 699 - 722, August - September, 2007, [Get Paper].

Abstract: 6D SLAM (Simultaneous Localization and Mapping) or 6D Concurrent Localization and Mapping of mobile robots considers six dimensions for the robot pose, namely, the x, y and z coordinates and the roll, yaw and pitch angles. Robot motion and localization on natural surfaces, e.g., driving outdoor with a mobile robot, must regard these degrees of freedom. This paper presents a robotic mapping method based on locally consistent 3D laser range scans. Iterative Closest Point (ICP) scan matching, combined with a heuristic for closed loop detection and a global relaxation method, results in a highly precise mapping system. A new strategy for fast data association, cached kd tree search, leads to feasible computing times. With no ground-truth data available for outdoor environments, point relations in maps are compared to numerical relations in uncalibrated aerial images in order to assess the metric validity of the resulting 3D maps.

Andreas Nüchter, Kai Lingemann and Joachim Hertzberg. 6D SLAM with Kurt3D, Robotics Today, Society of Manufacturing Engineers, First Quarter, Vol. 20, No. 1, ISSN 0193-6913, April, 2007, [Get Paper (PDF)].

Abstract: 6D SLAM (Simultaneous Localization and Mapping) or 6D Concurrent Localization and Mapping of mobile robots considers six dimensions for the robot pose, namely, the x, y and z coordinates and the roll, yaw and pitch angles. Robot motion and localization on natural surfaces, e.g., when driving with a mobile robot outdoor, must regard these degrees of freedom. 3D (6 DOF) scan matching, combined with a heuristic for closed loop detection and a global relaxation method, results in a highly precise mapping system for outdoor environments. The mobile robot Kurt3D is capable to run the mapping process with its on-board sensors and computers and is used to digitalize different environments. This paper summarizes our previous research.

Andreas Nüchter, Kai Lingemann, Joachim Hertzberg, Oliver Wulf, Bernardo Wagner, Kai Pervölz, Hartmut Surmann, Thomas Christaller. The RoboCup Rescue Team Deutschland1, KI – Künstliche Intelligenz No. 2, pp. 24 - 29, ISSN 0933-1875, May 2006. [Get Paper (PDF)]

Abstract: The RoboCup Rescue competition aims at boosting research in robots and infrastructure able to help in real rescue missions. The task is to find and report victims in areas of different grades of roughness, which are currently indoor. It challenges to some extreme the mobility of robot platforms as well as the autonomy of their control and sensor interpretation software. In the 2004 competition, the Kurt3D robot was introduced, the first participant capable of mapping its environment in 3D and self-localizing in all six degrees of freedom, i.e., x, y, z positions and roll, yaw and pitch angles. In 2005, we have upgraded the system with more sensors, with a focus on speeding up the algorithms, and we have started to develop a tracked robot platform to cooperate with Kurt3D. This paper gives an introduction to the competition in general and presents main contributions of our Deutschland1 RoboCup Rescue team.

Sandor P. Fekete, Rolf Klein, and Andreas Nüchter. Online searching with an autonomous robot, in Computational Geometry: Theory and Applications (CGTA) . Elsevier Science, Vol. 34, Issue 2, pp. 102-115, ISSN 0925-7721, May 2006 [Get Paper (PDF)].

Abstract: We discuss online strategies for visibility-based searching for an ob ject hidden behind a corner, using Kurt3D, a real autonomous mobile robot. This task is closely related to a number of well-studied problems. Our robot uses a threedimensional laser scanner in a stop, scan, plan, go fashion for building a virtual three-dimensional environment. Besides planning trajectories and avoiding obstacles, Kurt3D is capable of identifying objects like a chair. We derive a practically useful and asymptotically optimal strategy that guarantees a competitive ratio of 2, which differs remarkably from the well-studied scenario without the need of stopping for surveying the environment. Our strategy is used by Kurt3D, documented in a separate video.

Kai Lingemann, Hartmut Surmann, Andreas Nüchter, and Joachim Hertzberg. Verfahren zur Ermittlung der Position und Orientierung eines navigierenden Systems. Offenlegungsschrift DE 10 2004 015 111 A1 2005.10.20, Deutsches Patentamt. Offenlegungstag 20.10.2005 [Get Paper] [European Patent office]

Abstract: Bei dem Verfahren zur Ermittlung der Position und Orientierung eines autonom navigierenden Systems, beispielsweise eines Roboters, in einer Umgebung werden die Entfernung des in Fahrtrichtung vor den navigierenden System liegenden Bereichs der Umgebung bei Bewegung des navigierenden Systems abgetastet und die abgetasteten Entfernungspunkte mindestens zweier aufeinanderfolgender Abtastvorgänge als Entfernungsmesskurven in der Polardarstellung gespeichert. Anschliessend werden die Entfernungsmesskurven der beiden aufeinander folgenden Abtastvorgänge auf charakteristische merkmale wie z.B. Extremwerte untersucht. Danach werden die parameter von einender getrennt durchführbaren Translations- und Rotationstransformationen der einen Entfernungsmesskurve zur Ermittlungder zuordnung der charakteristischen Merkmale der trnasformierten Entfernungsmesskurve zu solchen der anderen Entfernungsmesskurve und die Position und Orientierung des navigierenden Systems anhand von dessen Position und dessen Orientierung zum Zeitpunkt des zeitlich ersten von zwei aufeinanderfolgenden Abtastungen sowie der ermittelten Parameter der Translation- und Rotationstransformation bestimmt.

Hartmut Surmann, Kai Pervölz, Andreas Nüchter, Kai Lingemann, Joachim Hertzberg, and Matthias Hennig. Simultaneous Mapping and Localization of Rescue Environments in it- Information Technology 47 (2005) 5, pages 282 - 291, Oldenbourg press, ISSN 1611-2776, October 2005. (Note: The paper is an extended version of the SSRR 2005 best paper awarded paper "Mapping of Rescue Environments with Kurt3D")

Simone Frintrop, Erich Rome, Andreas Nüchter, and Hartmut Surmann, A Bimodal Laser-Based Attention System. Journal Computer Vision and Image Understanding (CVIU), Special Issue on Attention and Performance in Computer Vision, Elsevier Science, 100(1-2):124-151, ISSN 1077-3142, October - November 2005.

Abstract: In this paper, we present a new bimodal attention system for robotic applications capable of processing data from different sensor modes simultaneously. Considering several sensor modalities is an obvious approach to regard a variety of ob ject properties. Nevertheless, conventional att ention systems only regard the processing of camera images. In contrast to these systems, the input data to our system is provided by a bimodal 3D laser scanner, mounted on top of an autonomous mobile robot. In a single 3D scan pass, the scanner yields range as well as reflectance data. Both dat a modes are illumination independent, yielding a robust approach that enables all day operation. Data from both laser modes are fed into our attention system built on principles of one of the standard models of visual attention by Koch & Ullman. The system computes conspicuities of both modes in parallel and fuses them into one saliency map. The focus of attention is directed to the most salient points in this map sequentially. We present results on recorded scans of indoor and outdoor scenes showing the respective advantages of the sensor modalities enabling the mode-specific detectio n of different ob ject properties. Furthermore, we show as an application of the attention system the recognition of ob jects for building semantic 3D maps of the robot's environment. Key words: visual attention, saliency detection, bimodal sensor fusion, 3D laser scanner

Kai Lingemann, Andreas Nüchter, Joachim Hertzberg, and Hartmut Surmann. High-Speed Laser Localization for Mobile Robots, Journal Robotics and Autonomous Systems (JRAS), Elsevier Science, 51(4):275-296, 2005 [ScienceDirect link] [Get Paper (PDF)].

Abstract: This paper describes a novel, laser-based approach for tracking the pose of a high-speed mobile robot. The algorithm is outstanding in terms of accuracy and computation time. The efficiency is achieved by a closed-form solution for the matching of two laser scans, the use of natural scan features and fast linear filters. The implemented algorithm is evaluated with the high-speed robot Kurt3D (4 m/s), and compared to standard scan matching methods in indoor and outdoor environments. Keywords: Localization; Pose tracking; Autonomous mobile robots; Scan matching; High-speed robotics.

Hartmut Surmann, Andreas Nüchter, Kai Lingemann, and Joachim Hertzberg. Kurt3D - An Autonomous Mobile Robot for Modelling the World in 3D, in ERCIM NEWS 55 : 24 - 25, ISSN 0926-4981, October 2003, [online article] [Get Magazine (PDF)] [Get Paper (PDF)].

Abstract: Kurt3D is an autonomous mobile robot equipped with a reliable and precise 3D laser scanner that digitalizes environments. High quality geometric 3D maps with semantic information are automatically generated after the exploration by the robot.

Hartmut Surmann, Andreas Nüchter, and Joachim Hertzberg. An autonomous mobile robot with a 3D laser range finder for 3D exploration and digitalization of indoor environments, Journal Robotics and Autonomous Systems (JRAS), Elsevier Science, Vol. 45, Issue 3-4, ISSN 0921-8890, pages 181 - 198, December 2003, [Get Paper (PDF)].

Abstract: Digital 3D models of the environment are needed in rescue and inspection robotics, facility managements and architecture. This paper presen ts an automatic system for gaging and digitalization of 3D indoor environments. It consists of an autonomous mobile robot, a reliable 3D laser range finder and three elaborated software modules. The first module, a fast variant of the Iterative Closest Points algorithm, registers the 3D scans in a common coordinate system and relocalizes the robot. The second module, a next best view planner, computes the next nominal pose based on the acquired 3D data while avoiding complicated obstacles. The third module, a closed-loop and globally stable motor controller, navigates the mobile robot to a nominal pose on the base of odometry and avoids collisions with dynamical obstacles. The 3D laser range finder acquires a 3D scan at this pose. The proposed method allows one to digitalize large indoor environments fast and reliably without any intervention and solves the SLAM problem. The results of two 3D digitalization experiments are presented using a fast octree-based visualization method. Keywords: Autonomous mobile robots; 3D laser range finder; Scan matching; Next best view planning; 3D digitalization; 3D gaging; Robot relocalization; SLAM

Oliver Struckmeier, Dorit Borrmann, Andreas Nüchter. Teach-In für die 3D-Scan Akquise mit einem Roboter. in Photogrammetrie Laserscanning Optische 3D-Messtechnik, Beiträge der Oldenburger 3D-Tage 2017, Jade Hochschule, pages 280-289, ISBN 978-3-87907-625-7, Wichmann Verlag, February 2017. [Get Paper].

Zusammenfassung: Die 3D-Erfassung einer kompletten Umgebung mittels 3D-Laserscanner stellt abhängig von der zu scannenden Umgebung und dem Scanner einen hohen Zeitaufwand für einen menschlichen Operator dar. Der Scanner muss an die einzelnen Scanpositionen bewegt und dort verortet werden. Mit steigender Qualität der Messung nimmt zudem die Dauer der einzelnen Scanvorgänge zu. In diesem Beitrag wird ein Teach-In Ansatz vorgestellt und evaluiert, der den manuellen Vorgang verkürzt. Dabei führt ein Roboter die vom Vermesser geplanten und eingespeicherten zeitintensiven Schritte automatisch durch und entlastet somit den Bediener.

Andreas Nüchter, Michael Bleier, Johannes Schauer, and Peter Janotta. Improving Google's Cartographer 3D Mapping by Continuous-Time SLAM, In Proceedings of the 6th ISPRS International Workshop 3D-ARCH 2017: "3D Virtual Reconstruction and Visualization of Complex Architectures", Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-2/W3, 543-549, Nafplio, Greece, March 2017, [Get Paper], [Get Paper].

Abstract: This paper shows how to use the result of Google's SLAM solution, called Cartographer, to bootstrap our continuous-time SLAM algorithm. The presented approach optimizes the consistency of the global point cloud, and thus improves on Google's results. We use the algorithms and data from Google as input for our continuous-time SLAM software. We also successfully applied our software to a similar backpack system which delivers consistent 3D point clouds even in absence of an IMU.

Michael Bleier and Andreas Nüchter. Low-cost 3D Laser Scanning in Air or Water Using Self-calibrating Structured Light, In Proceedings of the 6th ISPRS International Workshop 3D-ARCH 2017: "3D Virtual Reconstruction and Visualization of Complex Architectures", Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-2/W3, 105-112, Nafplio, Greece, March 2017, [Get Paper], [Get Paper].

Abstract: In-situ calibration of structured light scanners in underwater environments is time-consuming and complicated. This paper presents a self-calibrating line laser scanning system, which enables the creation of dense 3D models with a single fixed camera and a freely moving hand-held cross line laser projector. The proposed approach exploits geometric constraints, such as coplanarities, to recover the depth information and is applicable without any prior knowledge of the position and orientation of the laser projector. By employing an off-the-shelf underwater camera and a waterproof housing with high power line lasers an affordable 3D scanning solution can be built. In experiments the performance of the proposed technique is studied and compared with 3D reconstruction using explicit calibration. We demonstrate that the scanning system can be applied to above-the-water as well as underwater scenes.

Helge A. Lauterbach, Dorit Borrmann, and Andreas Nüchter. Towards Radiometrical Alignment of 3D Point Clouds, In Proceedings of the 6th ISPRS International Workshop 3D-ARCH 2017: "3D Virtual Reconstruction and Visualization of Complex Architectures", Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-2/W3, 419-424, Nafplio, Greece, March 2017, [Get Paper], [Get Paper].

Abstract: 3D laser scanners are typically not able to collect color information. Therefore coloring is often done by projecting photos of an additional camera to the 3D scans. The capturing process is time consuming and therefore prone to changes in the environment. The appearance of the colored point cloud is mainly effected by changes of lighting conditions and corresponding camera settings. In case of panorama images these exposure variations are typically corrected by radiometrical aligning the input images to each other. In this paper we adopt existing methods for panorama optimization in order to correct the coloring of point clouds. Therefore corresponding pixels from overlapping images are selected by using geometrically closest points of the registered 3D scans and their neighboring pixels in the images. The dynamic range of images in raw format allows for correction of large exposure differences. Two experiments demonstrate the abilities of the approach.

Rainer Koch, Stefan May, and Andreas Nüchter. Detection and Purging of Specular Reflective and Transparent Object Influences in 3D Range Measurements, In Proceedings of the 6th ISPRS International Workshop 3D-ARCH 2017: "3D Virtual Reconstruction and Visualization of Complex Architectures", Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-2/W3, 377-384, Nafplio, Greece, March 2017, [Get Paper], [Get Paper].

Abstract: 3D laser scanners are favoured sensors for mapping in mobile service robotics at indoor and outdoor applications, since they deliver precise measurements at a wide scanning range. The resulting maps are detailed since they have a high resolution. Based on these maps robots navigate through rough terrain, fulfil advanced manipulation, and inspection tasks. In case of specular reflective and transparent objects, e.g., mirrors, windows, shiny metals, the laser measurements get corrupted. Based on the type of object and the incident angle of the incoming laser beam there are three results possible: a measurement point on the object plane, a measurement behind the object plane, and a measurement of a reflected object. It is important to detect such situations to be able to handle these corrupted points. This paper describes why it is difficult to distinguish between specular reflective and transparent surfaces. It presents a 3D- Reflection-Pre-Filter Approach to identify specular reflective and transparent objects in point clouds of a multi-echo laser scanner. Furthermore, it filters point clouds from influences of such objects and extract the object properties for further investigations. Based on an Iterative-Closest-Point-algorithm reflective objects are identified. Object surfaces and points behind surfaces are masked according to their location. Finally, the processed point cloud is forwarded to a mapping module. Furthermore, the object surface corners and the type of the surface is broadcasted. Four experiments demonstrate the usability of the 3D-Reflection-Pre-Filter. The first experiment was made in a empty room containing a mirror, the second experiment was made in a stairway containing a glass door, the third experiment was made in a empty room containing two mirrors, the fourth experiment was made in an office room containing a mirror. This paper demonstrate that for single scans the detection of specular reflective and transparent objects in 3D is possible. It is more reliable in 3D as in 2D. Nevertheless, collect the data of multiple scans and post-filter them as soon as the object was bypassed should pursued. This is why future work concentrates on implementing a post-filter module. Besides, it is the aim to improve the discrimination between specular reflective and transparent objects.

Andreas Nüchter. Effiziente Speicherung großer Punktwolken - Datenstrukturen für Algorithmen für mobile und terrestrische Laserscansysteme. in Terrestrisches Laserscanning 2016, Beiträge zum 154. DVW-Seminar, Schriftenreihe des DVW, Band 85, Wißner Verlag, ISBN 978-3-95786-106-1, pages 105-120, November 2017, [Get Book].

Johannes Schauer, Janusz Bedkowski, Karol Majek, and Andreas Nüchter. Performance comparison between state-of-the-art point-cloud based collision detection approaches on the CPU and GPU. in Proceedings of the 4th IFAC Symposium on Telematics Applications (TA '16), Porto Alegre, Brazil, November 2016, [Get Paper].

Abstract: We present two fundamentally different approaches to detect collisions between two point clouds and compare their performance on multiple datasets. A collision between points happens if they are closer to each other than a given threshold radius. One approach utilizes the main CPU with a k-d tree datastructure to efficiently carry out fixed range searches around points in 3D while the other mainly executes on a GPU using a regular grid decomposition technique implemented in the CUDA framework. We will show how massively parallel 3D range searches on a grid based datastructure on a GPU performs similarly well as a tree based approach on the CPU with orders of magnitude less parallelization. We also show how each method scales with varying input sizes and how they perform differently well depending on the spatial structure of the input data.

Florian Leutert, Dorit Borrmann, Klaus Schilling, and Andreas Nüchter. Spatial projection of thermal data for visual inspection. In Proceedings of the 14th International Conference on Control, Automation, Robotics and Vision (ICARCV ’16), Phuket, Thailand, November 2016, [Get Paper].

Abstract: Since the advent of thermal imaging, devices with a high optical resolution that use detector arrays to capture the emitted radiance in the thermal infrared range of an entire scene simultaneously have developed as a standard in monitoring energy related. They have had a huge impact on the building industry and in manifacturing, where they are commonly used to monitor proecces that require stable temperature conditions. As beneficial as contactless measurements are, the subsequent localization of points of interest in the environment is often difficult. To overcome this problem we propose a portable system that combines thermal imaging with Augmented Reality (AR). The idea of the approach is to project the gathered temperature information back into the scene to facilitate visual inspection.

Ville Lehtola, Juho-Pekka Virtanen, Petri Rönnholm, Andreas Nüchter. LOCALIZATION CORRECTIONS FOR MOBILE LASER SCANNER USING LOCAL SUPPORT-BASED OUTLIER FILTERING. in Proceedings of the ISPRS Congress 2016, ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., Prague, Czech Republic, 2016, [Get Paper],

Abstract: Following the pioneering work introduced in [Lehtola et al., ISPRS J. Photogramm. Remote Sens. 99, 2015, pp. 25–29], we extend the state-of-the-art intrinsic localization solution for a single two-dimensional (2D) laser scanner from one into (quasi) three dimensions (3D). By intrinsic localization, we mean that no external sensors are used to localize the scanner, such as inertial measurement devices (IMU) or global navigation satellite systems (GNSS). Specifically, the proposed method builds on a novel concept of local support-based filtering of outliers, which enables the use of six degrees-of-freedom (DoF) simultaneous localization and mapping (SLAM) for the purpose of enacting appropriate trajectory corrections into the previous one-dimensional solution. Moreover, the local support-based filtering concept is platform independent, and is therefore prone to be widely generalizable. The here presented overall method is yet limited into quasi-3D by its inability to recover trajectories with steep curvature, but in the future, it may be further extended into full 3D.

Dorit Borrmann, Florian Leutert, Ivan Maurovic, Marija Seder, Andreas Nüchter. Automatische Grundrisserstellung mittels Laserscandaten. in Photogrammetrie Laserscanning Optische 3D-Messtechnik, Beiträge der Oldenburger 3D-Tage 2016, Jade Hochschule, pages 108-119, ISBN 978-3-87907-604-8, Wichmann Verlag, February 2016. [Get Paper].

Zusammenfassung: In den letzten Jahren haben sich Laserscanner zum Stand der Technik bei der Erstellung von Gebäudemodellen entwickelt. Im Gegensatz zur vergleichsweise kurzen Aufnahmezeit bei der eigentlichen Erfassung der Umgebung mit dem Scanner nimmt die Nachbearbeitung der Daten einen deutlich höheren Zeitanteil ein. Eine manuelle Datenanalyse ist zeitaufwändig und fehleranfällig. Dies erhöht den Bedarf an automatischen Verfahren zur quantitativen Erfassung und Charakterisierung von Umgebungen.
In diesem Beitrag präsentieren wir eine automatische Grundrisserstellung basierend auf dem 3D Toolkit (3DTK - www.threedtk.de). Nach der autonomen Akquise mit einem mobilen Roboter werden die Daten mittels des iterativen Verfahrens der nächsten Punkte (engl. Iterative Closest Point (ICP)) registriert. Anschließend erfolgt eine automatische Vektorisierung eines 2D-Schnitts der Umgebung basierend auf Verfahren aus der Bildverarbeitung. Der so erzeugte Grundriss dient als Grundlage für eine semantische Karte.

Christian Pfitzner, Stefan May and Andreas Nüchter. Neural Network-based Visual Body Weight Estimation for Drug Dosage Finding, In Proceedings of the SPIE 9784, Medical Imaging 2016: Image Processing, doi:10.1117/12.2216042 San Diego, CA, USA, February 2016.

Abstract: Body weight adapted drug dosages are important for emergency treatments. This paper describes an improved body weight estimation approach for emergency patients in a trauma room, based on images from a RGBD sensor and a thermal camera. The improvements are archived by several extensions: The sensor fusion of RGBD and thermal camera eases filtering and segmentation of the patient's body from the background. Robustness and accuracy is gained by an artificial neural network (ANN), which considers features from the sensors as input to calculate the patient's body weight, e.g. the patient's volume, surface and shape parameters. The ANN is trained offline with 30 percent of the patients data. Preliminary experiments with 69 real patients show an accuracy close to 90 percent for a threshold of ten percent relative error in real body estimation. Results are compared to the patient's self estimation, a physician's guess and an anthropometric method: If the patient is knowledgeable it is the best possibility for body weight adapted drug dosages with 97 percent accuracy. The treating physicians and the anthropometric estimation achieve an accuracy of approximately 70 percent. The here presented approach gets an accuracy of nearly 90 percent and would be the best solution if a patient can not provide his own body weight and can not be weighted on a scale. These preliminary results demonstrate a sufficient approach for an upcoming clinical trial with 1,000 patients for body weight estimation.

Rainer Koch, Stefan May, Philipp Koch, Markus Kühn, and Andreas Nüchter. Detection of Specular Reflections in Range Measurements for Faultless Robotic SLAM, In Proceedings of ROBOT'2015: Second Iberian Robotics Conference, Lisbon, Portugal, Volume 417 of the series Advances in Intelligent Systems and Computing pp 133-145, 2015, [Get Paper].

Abstract: Laser scanners are state-of-the-art devices used for mapping in service, industry, medical and rescue robotics. Although a lot of work has been done in laser-based SLAM, maps still suffer from interferences caused by objects like glass, mirrors and shiny or translucent surfaces. Depending on the surface's reflectivity, a laser beam is deflected such that returned measurements provide wrong distance data. At certain positions phantom-like objects appear. This paper describes a specular reflectance detection approach applicable to the emerging technology of multi-echo laser scanners in order to identify and filter reflective objects. Two filter stages are implemented. The first filter reduces errors in current scans on the fly. A second filter evaluates a set of laser scans, triggered as soon as a reflective surface has been passed. This makes the reflective surface detection more robust and is used to refine the registered map. Experiments demonstrate the detection and elimination of reflection errors. They show improved localization and mapping in environments containing mirrors and large glass fronts is improved.

HamidReza Houshiar and Andreas Nüchter. 3D Point Cloud Compression using Conventional Image Compression for Efficient Data Transmission. In Proceedings of the XXV International Symposium on Information, Communication and Automation Technologies (ICAT '15), IEEE Xplore, Sarajevo, Bosnia, October 2015, [Get Paper (PDF)].

Abstract: Modern 3D laser scanners make it easy to collect large 3D point clouds. In this paper we present the use of conventional image based compression methods for 3D point clouds. We map the point cloud onto panorama images to encode the range, reflectance and color value for each point. An encoding method is presented to map the floating point measured ranges on to a three channel image. The image compression methods are used to compress the generated panorama images. We present the results of several lossless compression methods and the lossy JPEG on point cloud compression. Lossless compression methods are designed to retain the original data. On the other hand lossy compression methods sacrifice the details for higher compression ratio. This produces artefacts in the recovered point cloud data. We study the effects of these artefacts on encoded range data. A filtration process is presented for determination of range outliers from uncompressed point clouds.

Andreas Nüchter, Dorit Borrmann, Philipp Koch, Markus Kühn, Stefan May. A Man-Portable, IMU-free Mobile Mapping System. in Proceedings of the ISPRS Geospatial Week 2015, Laserscanning 2015, ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., II-3/W5, 17-23, La Grande Motte, France 2015, [Get Paper], [Get Paper],

Abstract: Mobile mapping systems are commonly mounted on cars, ships and robots. The data is directly geo-referenced using GPS data and expensive IMU (inertial measurement systems). Driven by the need for flexible, indoor mapping systems we present an inexpensive mobile mapping solution that can be mounted on a backpack. It combines a horizontally mounted 2D profiler with a constantly spinning 3D laser scanner. The initial system featuring a low-cost MEMS IMU was revealed and demonstrated at MoLaS: Technology Workshop Mobile Laser Scanning at Fraunhofer IPM in Freiburg in November 2014. In this paper, we present an IMU-free solution.

Hamidreza Houshiar, Dorit Borrmann, Jan Elseberg, Andreas Nüchter, Falk Näth, Stephan Winkler. CASTLE3D - A COMPUTER AIDED SYSTEM FOR LABELLING ARCHAEOLOGICAL EXCAVATIONS IN 3D. Proceedings of 25th CiPA Symposium, ISPRS Annals Photogrammetry and Remote Sensing Spatial Inf. Sci., II-5/W3, DOI 10.5194/isprsannals-II-5-W3-111-2015, pages 111-118, Taipei, Taiwan, September 2015. [Get Paper].

Abstract: Documentation of archaeological excavation sites with conventional methods and tools such as hand drawings, measuring tape and archaeological notes is time consuming. This process is prone to human errors and the quality of the documentation depends on the qualification of the archaeologist on site. Use of modern technology and methods in 3D surveying and 3D robotics facilitate and improve this process. Computer-aided systems and databases improve the documentation quality and increase the speed of data acquisition. 3D laser scanning is the state of the art in modelling archaeological excavation sites, historical sites and even entire cities or landscapes. Modern laser scanners are capable of data acquisition of up to 1 million points per second. This provides a very detailed 3D point cloud of the environment. 3D point clouds and 3D models of an excavation site provide a better representation of the environment for the archaeologist and for documentation. The point cloud can be used both for further studies on the excavation and for the presentation of results. This paper introduces a Computer aided system for labelling archaeological excavations in 3D (CASTLE3D). Consisting of a set of tools for recording and georeferencing the 3D data from an excavation site, CASTLE3D is a novel documentation approach in industrial archaeology. It provides a 2D and 3D visualisation of the data and an easy-to-use interface that enables the archaeologist to select regions of interest and to interact with the data in both representations. The 2D visualisation and a 3D orthogonal view of the data provide cuts of the environment that resemble the traditional hand drawings. The 3D perspective view gives a realistic view of the environment. CASTLE3D is designed as an easy-to-use on-site semantic mapping tool for archaeologists. Each project contains a predefined set of semantic information that can be used to label findings in the data. Multiple regions of interest can be joined under one label. Further information such as color, orientation and archaeological notes are added to the label to improve the documentation. The available 3D information allows for easy measurements in the data. The full 3D information of a region of interest can be segmented from the entire data. By joining this data from different georeferenced views the full 3D shape of findings is stored. All the generated documentation in CASTLE3D is exported to an XML format and serves as input for other systems and databases. Apart from presenting the functionalities of CASTLE3D we evaluate its documentation process in a sample project. For this purpose we export the data to the Adiuvabit database (http://adiuvabit.de) where more information is added for further analysis. The documentation process is compared to traditional documentation methods and it is shown how the automated system helps in accelerating the documentation process and decreases errors to a minimum.

Dorit Borrmann, Robin Hess, Daniel Eck, HamidReza Houshiar, Andreas Nüchter, and Klaus Schilling. Evaluation of Methods for Robotic Mapping of Cultural Heritage Sites, In Proceedings of the 2th IFAC conference on Embedded Systems, Computer Intelligence and Telematics (CESCIT '15), Maribor, Slovenia 2015,

Abstract: In archaeological studies the use of new technologies has moved into focus in the past years creating new challenges such as the processing of the massive amounts of data. In this paper we present steps and processes for smart 3D modelling of environments by use of the mobile robot Irma3D. A robot that is equipped with multiple sensors, most importantly a photo camera and a laser scanner, enables the automation of most of the processes, including data acquisition and registration. The robot was tested in the Würzburg Residence. Methods for automatic 3D color reconstructions of cultural heritage sites are evaluated in this paper.

Philipp Koch, Stefan May Michael Schmidpeter, Markus Kühn, Christian Pfitzner, Christian Merkl, Rainer Koch, Martin Fees, Jon Martin, and Andreas Nüchter. Multi-Robot Localization and Mapping based on Signed Distance Functions, Proceedings of the IEEE International Conference on Autonomous Robot Systems and Competitions (ICARSC '15), pages 77-82, Villa Real, Portugal, April 2015, [Get Paper].

Abstract: This publication describes a 2D Simultaneous Localization and Mapping approach applicable to multiple mobile robots. The presented strategy uses data of 2D LIDAR sensors to build a dynamic representation based on Signed Distance Functions. A multi-threaded software architecture performs registration and data integration in parallel allowing for drift-reduced pose estimation of multiple robots. Experiments are provided demonstrating the application with single and multiple robot mapping using simulated data, public accessible recorded data as well as two actual robots operating in a comparably large area.

Christian Pfitzner, Stefan May, Christian Merkl, Lorenz Breuer, Martin Köhrmann, Joel Braun, Franz Dirauf, and Andreas Nüchter. Libra3D: Body Weight Estimation for Emergency Patients in Clinical Environment with a 3D Structured Light Sensor, in Proceedings of the IEEE International Conference Robotics and Automation (ICRA '15), pages 2888 - 2893, Seattle, WA, USA, May 2015, [Get Paper].

Abstract: This paper describes the application of a weight estimation method for emergency patients in clinical environment. The approach applies established algorithms for point cloud processing and filtering on data from a low-cost structured light sensor. The patient's volume is estimated on the basis of his visible front surface. The approach is currently put to test in the workflow of the emergency room at the Universitätsklinikum Erlangen, Germany. Preliminary results show the accuracy of the approach in relation to other conservative means of weight measurements, like for example by physicians and anthropometric measurements.

Janis Gailis and Andreas Nüchter. Towards Globally Consistent Scan Matching With Ground Truth Integration, In Proceedings of the ISPRS International Conference on Photogrammetric Image Analysis (PIA '15), Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XL-3/W2, pages 59-64, Munich, Germany, March 2015, [Get Paper].

Abstract: The scan matching based simultaneous localization and mapping method with six dimensional poses is capable of creating a three dimensional point cloud map of the environment, as well as estimating the six dimensional path that the vehicle has traveled. The essence of it is the registering and matching of sequentially acquired 3D laser scans, while moving along a path, in a common coordinate frame in order to provide 6D pose estimations at the respective positions, as well as create a three dimensional map of the environment. An approach that could drastically improve the reliability of acquired data is to integrate available ground truth information. This paper is about implementing such functionality as a contribution to 6D SLAM (simultaneous localization and mapping with 6 DoF) in the 3DTK -- The 3D Toolkit software, as well as test the functionality of the implementation using real world datasets.

Dorit Borrmann, Robin Hess, Daniel Eck, Andreas Nüchter, and Klaus Schilling. Robotic Mapping of Cultural Heritage Sites, In Proceedings of the 5th ISPRS International Workshop 3D-ARCH 2015: "3D Virtual Reconstruction and Visualization of Complex Architectures", Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XL-5/W4, pages 9-16, Avila, Spain, February 2015, [Get Paper], [Get Paper].

Abstract: In archaeological studies the use of new technologies has moved into focus in the past years creating new challenges such as the processing of the massive amounts of data. In this paper we present steps and processes for smart 3D modelling of environments by use of the mobile robot Irma3D. A robot that is equipped with multiple sensors, most importantly a photo camera and a laser scanner, enables the automation of most of the processes, including data acquisition and registration. The robot was tested in two scenarios, Ostia Antica and the W\"urzburg Residence. The paper describes the steps for creating 3D color reconstructoins of these reknown cultural heritage sites.

Phil Käshammer and Andreas Nüchter. Mirror Identification and Correction of 3D Point Clouds, In Proceedings of the 5th ISPRS International Workshop 3D-ARCH 2015: "3D Virtual Reconstruction and Visualization of Complex Architectures", Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XL-5/W4,, Avila, Spain, February 2015, [Get Paper], [Get Paper].

Abstract: In terrestrial laser scanning (TLS), the surface geometry of objects is scanned by laser beams and recorded digitally. This produces a discrete set of scan points, commonly referred to as a point cloud. The coordinates of the scan points are determined by measuring the angles and the time-of-flight relative to the origin (scanner position). However, if it comes to mirror surfaces laser beams are fully reflected, due to the high reflectivity. Mirrors do not appear in the point cloud at all. Instead, for every reflected beam, a incorrect scan point is created behind the actual mirror plane. Consequently, problems arise in multiple derived application fields such as 3D virtual reconstruction of complex architectures. The paper presents a new approach to automatically detect framed rectangular mirrors with known dimensions and to correct the 3D point cloud, using the calculated mirror plane.

Stefan May, Philipp Koch, Rainer Koch, Christian Merkl, Christian Pfitzer, and Andreas Nüchter. A Gereralized 2D and 3D Multi-Sensor Data Integration Approach based on Signed Distance Functions for Multi-Modal Robotic Mapping. In Proceedings of th 19th International Workshop on Vision, Modeling and Visualization (VMV '14), Darmstadt, October 2014. [Get Paper] [Get Paper].

Abstract: This paper describes a data integration approach for arbitrary 2D/3D depth sensing units exploiting assets of the signed distance function. The underlying framework generalizes the KinectFusion approach with an object-oriented model respecting different sensor modalities. For instance, measurements of 2D/3D laser range finders and RGB-D cameras can be integrated into the same representation. Exemplary, an environment is reconstructed with a 3D laser range finder, while adding fine details from objects of interest by closer inspection with an \mbox{RGB-D} sensor. A typical application of this approach is the exploration in rescue environments, where large-scale mapping is performed on the basis of long-range laser range finders while hollows are inspected with lightweight sensors attached to a manipulator arm.

Johannes Schauer and Andreas Nüchter. Efficient Point Cloud Collision Detection and Analysis in a Tunnel Environment using Kinematic Laser Scanning and k-d Tree Search. In Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XL-3,, Proceedings of Photogrametric Computer Vision (PCV '14), pages 289-295, Zurich, September 2014. [Get Paper] [Get Paper] [Get Poster].

Abstract: Measuring the structure gauge of tunnels and other narrow passages has so far been the only way to evaluate whether large vehicles can pass through them. But especially for very long vehicles like train wagons and their cargo, the structure gauge is an insufficient measure because the center part of the vehicle between two bogies will inevitably leave the swept volume of its cross section when moving along any other trajectory than a straight line perpendicular to its cross section. In addition, the vehicle as well as the cargo must keep a minimum safety margin from the environment at all points of its trajectory. This paper explores an automated method to check for possible collisions of a model represented by a 3D point cloud moving through the 3D point cloud of an environment. We were given environment data of a train track through a narrow tunnel where simply relying on the structure gauge would indicate that a given wagon would pass through without any collision even though in reality, the train wagon would collide with the inner tunnel wall inside a sharp turn of the tracks. The k-d tree based collision detection method presented in this paper is able to correctly highlight these collisions and indicate the penetration depth of each colliding point of the environment into the model of the train wagon. It can be generalized for any setup where two static point clouds have to be tested for intersection along a trajectory.

Janusz Będkowski, Karol Majek, and Andreas Nüchter. Nowy algorytm 6DSLAM wykorzystujący semantyczne rozpoznanie otoczenia. 13 Krajowka Konferencja Robotyki Kudowa Zdrój Prace Naukowe, Elektronika z. 194 Post&ecedil;py Robotyki Tom II, pages 513-520, ISSN 0137-2343, July 2014. [Get Paper].

Abstract: W artykule przedstawiono modyfikację algorytmu 6DSLAM wykorzystującą semantyczne rozpoznawanie otoczenia. Zastosowanie semantycznego podejścia nie tylko poprawia w porównaniu do klasycznej metody dokładność tworzonej mapy metrycznej przez robota mobilnego, ale także umożliwia tworzenie takiej mapy w trudnych warunkach terenowych. Przedstawiono eksperymenty tworzenia mapy metrycznej/semantycznej budynków uwzględniając jazdę poziomą oraz kierunku pionowym po schodach. Porównano wynik z poprzednią implementacją algorytmu 6DSLAM. Nowe podejście poprawia spójność oraz dokładność mapy metrycznej. Zastosowanie semantycznego rozpoznawania otoczenia pozwala na rozszerzenie mapy metrycznej o nowe informacje o charakterze jakościowym, w tym przypadku rozróżniane są ściany, podłoga, sufit oraz punkty charakteryzujące się otoczeniem nieuporządkowanym.

Jan Elseberg, Dorit Borrmann, Johannes Schauer, Andreas Andreas Nüchter, Dirk Koriath, and Ulrich Rautenberg. A sensor skid for precise 3D modeling of production lines.. in ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., II-5, Proceedings of ISPRS Technical Commission V Symposium "Close-range imaging, ranging and applications", pages 117-122, June 2014. [Get Paper] [Get Paper]

Abstract: Motivated by the increasing need of rapid characterization of environments in 3D, we designed and built a sensor skid that automates the work of an operator of terrestrial laser scanners. The system combines terrestrial laser scanning with kinematic laser scanning and uses a novel semi-rigid SLAM method. It enables us to digitize factory environments without the need to stop production. The acquired 3D point clouds are precise and suitable to detect objects that collide with items moved along the production line.

HamidReza Houshiar, Dorit Borrmann, and Andreas Nüchter. Fortlaufende semantische 3D-Kartierung von archäologischen Ausgrabungsstätten. in Photogrammetrie Laserscanning Optische 3D-Messtechnik, Beiträge der Oldenburger 3D-Tage 2014, Jade Hochschule, Wichmann Verlag, ISBN 978-3-87907-536-2, pages 268-277, February 2014.

Zusammenfassung: Das 3D Laserscanning ist Stand der Technik bei der Modellierung archäologischer Ausgrabungsstätten, historischer Anlagen und sogar ganzer Städte oder Landschaften. Die Dokumentation der Befunde auf einer Ausgrabungsstätte ist eine wesentliche archäologische Aufgabe. Ein automatisiertes System würde diesen Prozess beschleunigen und die Anzahl der Fehler auf ein Minimum reduzieren. Dieser Beitrag stellt einen neuen Ansatz in der Dokumentation industrieller Archäologie vor. Er besteht aus einer Reihe von Tools zur Erfassung und Registrierung von 3D-Daten auf Ausgrabungsstätten. Wir stellen ein effizientes Werkzeug zur Verfügung für die Visualisierung der erworbenen 3D-Punktwolken im 3D- und 2D-Modus. Der Hauptzweck dieser Software ist Archäologen ein einfach zu bedienendes Tool für die semantische Kartierung vor Ort zu bieten. Es enthält Funktionen für die Auswahl und Kennzeichnung von Funden. Jedes Label kann mit weiteren Informationen versehen werden. Diese Daten werden im XML-Format exportiert und dienen als Eingabe für andere Systeme und Datenbanken.

Gerd Bruder, Frank Steinicke, and Andreas Nüchter. Immersive Point Cloud Virtual Environments.. in Proceedings of IEEE Symposium on 3D User Interfaces 3DUI Proceedings of IEEE Symposium on 3D User Interfaces (3DUI '14), Poster, pages 161-162, March 2014. [Get Paper]

Abstract: Today’s three-dimensional (3D) virtual environments (VEs) are usually based on textured polygonal 3D models, which represent the appearance and geometry of the virtual world. However, some application domains require other graphical paradigms, which are currently not adequately addressed by 3D user interfaces. We in- troduce a novel approach for a technical human-robot telepresence setup that allows a human observer to explore a VE, which is a 3D reconstruction of the real world based on point clouds. Such point cloud virtual environments (PCVEs) represent the external environ- ment, and are usually acquired by 3D scanners. We present an ap- plication scenario, in which a mobile robot captures 3D scans of a terrestrial environment, which are automatically registered to a co- herent PCVE. This virtual 3D reconstruction is displayed in an im- mersive virtual environment (IVE) in which a user can explore the PCVE. We explain and describe the technical setup, which opens up new vistas of presenting a VE as points rather than a polygonal representation.

Dorit Borrmann, HamidReza Houshiar, Jan Elseberg, Andreas Nüchter, Falk Näth, and Stephan Winkler. Fortlaufende semantische 3D-kartierung von archäologischen Ausgrabungsstätten. in Photogrammetrie Laserscanning Optische 3D-Messtechnik, Beiträge der Oldenburger 3D-Tage 2014, Jade Hochschule, Wichmann Verlag, February 2014.

Abstract: Das 3D Laserscanning ist Stand der Technik bei der Modellierung archäologischer Ausgrabungsstätten, historischer Anlagen und sogar ganzer Städte oder Landschaften. Die Dokumentation der Befunde auf einer Ausgrabungsstätte ist eine wesentliche archäologische Aufgabe. Ein automatisiertes System würde diesen Prozess beschleunigen und die Anzahl der Fehler auf ein Minimum reduzieren. Dieser Beitrag stellt einen neuen Ansatz in der Dokumentation industrieller Archäologie vor. Er besteht aus einer Reihe von Tools zur Erfassung und Registrierung von 3D-Daten auf Ausgrabungsstätten. Wir stellen ein effizientes Werkzeug zur Verfügung für die Visualisierung der erworbenen 3D-Punktwolken im 3D- und 2D-Modus. Der Hauptzweck dieser Software ist Archäologen ein einfach zu bedienendes Tool für die semantische Kartierung vor Ort zu bieten. Es enthält Funktionen für die Auswahl und Kennzeichnung von Funden. Jedes Label kann mit weiteren Informationen versehen werden. Diese Daten werden im XML-Format exportiert und dienen als Eingabe für andere Systeme und Datenbanken.

Girum G. Demisse, Dorit Borrmann, and Andreas Nüchter. Interpreting Thermal 3D Models of Indoor Environments for Energy Efficiency, Proceedings of the 16th IEEE International Conference on Advanced Robotics (ICAR '13), Montevideo, Urugauy, November 2013. [Get Paper].

Abstract: In recent years, 3D models of buildings are used in maintenance and inspection, preservation, and other building related applications. However, the usage of these models is limited, because most models are pure representations with no or little associated semantics. In this paper, we present a pipeline of techniques used for interior interpretation, object detection, and adding energy related semantics to windows of a 3D thermal model. A sequence of algorithms is presented for building the fundamental semantics of a 3D model. Furthermore, a Markov Random Field is used to model the temperature distribution of detected windows to further label the windows as either open, closed or damaged.

Billy Okal and Andreas Nüchter. Sliced Curvature Scale Space for Representing and Recognizing 3D objects, Proceedings of the 16th IEEE International Conference on Advanced Robotics (ICAR '13), Montevideo, Uruguay, November 2013. [Get Paper].

Abstract: Perception plays a key role in the development of intelligent autonomous systems. In particular object recognition and registration tasks are crucial to any intelligent autonomous system such as autonomous cars or personal robots. The repre- sentation of 3D object sensor measurements largely affects the choice of higher level processing possible on the sensor data. We explore the use of scale space theory via the curvature scale space and extend it to represent 3D objects in our new SCSS (Sliced Curvature Scale Space) framework. We further develop techniques of further processing the SCSS representation including feature extraction and dimensionality reduction for use in learning frameworks. We perform an array of experiments to validate the effectiveness of our method and demonstrate recognition performance using support vector machines. The results indicate that our new representation retains the nice qualities of the original curvature scale space method while being robust and compact for 3D object representation and recognition.

HamidReza Houshiar, Jan Elseberg, Dorit Borrmann, Andreas Nüchter. Panorama Based Point Cloud Reduction and Registration, Proceedings of the 16th IEEE International Conference on Advanced Robotics (ICAR '13), Montevideo, Urugauy, November 2013. [Get Paper].

Abstract: To reconstruct environments 3D point clouds acquired by laser scanners are registered. This is an important but also time consuming part of any mapping system for mobile robots. The time needed for mapping is drastically reduced when the size of the input data is reduced. This paper examines different ways of reducing the size of point clouds without losing vital information for the matching process. We present novel point cloud reduction methods on the basis of panorama images. It is shown that the reduced point clouds are ideally suited for feature based registration on panorama images. We evaluate the presented reduction methods based on their effect on the performance of the registration algorithm.

Andreas Nüchter, Jan Elseberg, and Dorit Borrmann, Irma3D - An Intelligent Robot for Mapping Applications, Proceedings of the 3rd IFAC Symposium on Telematics Applications (TA '13), Volume 3, Part 1, doi:10.3182/20131111-3-KR-2043.00011, Seoul, Korea, November 2013. [Get Paper].

Abstract: Motivated by the increasing need of rapid characterization of environments in 3D, we designed a robot system that automates the work of an operator of terrestrial laser scanners. The built system enables to work without using special targets or markers and thus enables the surveyors to save more than 75% of the time spent in the field. Another impulse for developing the platform is the demand for a remote multi-sensor inspection tool. The robot is capable of surveying remote sites or danger areas, such as plants, underground mines, tunnels, caves, or channels. The results are precise, multi-modal digital 3D maps.
This paper presents the recently developed robot Irma3D, its hardware, the developed interconnected software modules, the associated sensor calibration methods and a few applications.

Jan Elseberg, Dorit Borrmann, and Andreas Nüchter. A Study of Scan Patterns for Mobile Mapping, Proceedings of the ISPRS Conference on "Serving Society with Geoinformatics" (ISPRS-SSG '13), Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XL-7/W2, 75-80, doi:10.5194/isprsarchives-XL-7-W2-75-2013, Antalya, Turkey, November 2013, [Get Paper].

Abstract: Mobile terrestrial scanning systems automate terrestrial laser scanning. Continous scanning mobile terrestrial systems constantly spin the terrestrial laser scanner and thus combine terrestrial scanning with kinematic laser scanning. This paper presents a scan pattern analysis for these systems. We aim at finding the most advantageous combination of terrestrial and kinematic systems. The resulting 3D point cloud depends on the scan pattern and the trajectory and velocity of the mobile system.

HamidReza Houshiar, Jan Elseberg, Dorit Borrmann, Andreas Nüchter, Stephan Winkler, and Falk Näth. On-site Semantic Mapping of Archeological Excavation Areas, ISPRS Annals Photogrammetry and Remote Sensing. Spatial Inf. Sci., II-5/W1, 163-168, Strasbourg, France, September 2013, DOI 10.5194/isprsannals-II-5-W1-163-2013, [Get Paper]

Abstract: 3D laser scanning is the state of the art in modeling archaeological excavation sites, historical sites and even entire cities or landscapes. The documentation of findings on an excavation site is an essential archaeological task. Automated systems accelerate this process and decrease the amount of error to a minimum. This paper presents a new documentation approach in industrial archaeology. It consist of a set of tools for recording and registering 3D data from excavation sites. We provide an efficient tool for visualization of acquired 3D point clouds in 3D and 2D modes. The main purpose of this software is to provide an easy to use, on-site semantic mapping tool for archaeologist. It includes functions for selecting and labeling findings. Additional information can be provided for each label. This data is exported to an XML format and serves as input for other systems and data bases.

Corina Gurau and Andreas Nüchter. Challenges in Using Semantic Knowledge for 3D Object Classification, in Proceedings of the KI 2013 Workshop on Visual and Spatial Cognition, KIK - KI & Kognition Workshop Series, Koblenz, Germany, September 2013, [Get Paper].

Abstract: To cope with a wide variety of tasks, robotic systems need to perceive and understand their environments. In particular, they need a representation of individual objects, as well as contextual relations between them. Visual information is the primary data source used to make predictions and inferences about the world. There exists, however, a growing tendency to introduce high-level semantic knowledge to enable robots to reason about objects. We use the Semantic Web framework to represent knowledge and make inferences about sensor data, in order to detect and classify objects in the environment. The contribution of this work is the identification of several challenges that co-occur when combining sensor data processing with such a reasoning method.

Liang Zhang, Qingquan Li, Ming Li, Q.Zh Mao, and Andreas Nüchter. Multiple Vehicle-like Target Tracking Based on Velodyne Lidar, in Proceedings of the 6th IFAC Symposium on Intelligent Autonomous Vehicles (IAV '13), Volume 8, Part 1, DOI 10.3182/20130626-3-AU-2035.00058, Gold Coast, Australia, June 2013, [Get Paper].

Abstract: This paper proposes a novel Multiple vehicle-like target tracking method based on Velodyne HDL64E Lidar. The proposed method combines multiple hypothesis tracking (MHT) algorithm and dynamic point cloud registration (DPCR), which is able to solve the multiple vehicle-like target tracking in highly dynamic urban environments without any auxiliary information from GPS or IMU. Specifically, to track targets consistently, the DPCR is developed to calculate accurate location and pose of the ego-vehicle for the translation of raw measurements in moving coordinate systems into a static absolute coordinate system; while in turn, MHT helps to improve the performance of DPCR by discriminating and removing the dynamic points from the scene. Furthermore, the proposed MHT method is also able to solve the occlusion problem existing in the point cloud. Experiments on sets of urban environments prove that the presented method is effective and robust, even in highly dynamic environments.

Dorit Borrmann, Pedro J. de Rezende, Cid C. de Souza, Sandor P. Fekete, Stephan Friedrich, Alexander Kröller, Andreas Nüchter, Christiane Schmidt, and Davi C. Tozoni. Point Guards and Point Clouds: Solving general Art Gallery Problems. in Proccedings of the 29th ACM Annual Symposium on Computational Geometry (SoCG '13), pp. 347-348, ISBN 978-1-4503-2031-3, Rio de Janeiro, Brazil, June 2013. [Get Paper] [Get Video].

Abstract: In this video, we illustrate how one of the classical areas of computational geometry has gained in practical relevance, which in turn gives rise to new, fascinating geometric problems. In particular, we demonstrate how the robot platform IRMA3D can produce high-resolution, virtual 3D environments, based on a limited number of laser scans. Computing an optimal set of scans amounts to solving an instance of the Art Gallery Problem (AGP): Place a minimum number of stationary guards in a polygonal region P, such that all points in P are guarded.

Dorit Borrmann, HamidReza Houshiar, Jan Elseberg, and Andreas Nüchter. Vom Kombinieren von 3D-Modellen mit Farb- und Temperaturinformationen. in Photogrammetrie Laserscanning Optische 3D-Messtechnik, Beiträge der Oldenburger 3D-Tage 2013, Jade Hochschule, Wichmann Verlag, February 2013.

Zusammenfassung: In den letzten Jahren wurden große Fortschritte bei der automatischen Registrierung unterschiedlicher Daten gemacht, zum Beispiel bei Laserscandaten, Fotos und Thermalbilder. So wurden zuverlässige Methoden entwickelt, um Daten aus einem einzelnen Aufnahmeprozess zu registrieren. Probleme bereiten jedoch Daten, die zu unterschiedlichen Zeiten aufgenommen wurden. Dies ist aber essentiell um wertvolle Informationen verschiedener Sensoren zu kombinieren und den Anforderungen an die einzelnen Sensoren gerecht zu werden. Verwertbare Informationen von Thermalbildern erhält man ausschließlich ohne störende Einflüsse des Sonnenlichts. Farbfotos hingegen werden optimal bei guten Farbverhältnissen aufgenommen. Laserscanner sind relativ robust gegenüber wechselnden Lichtverhältnissen. Für alle Sensoren ist ein Aufnahmezeitpunkt wünschenswert, zu dem möglichst wenige dynamische Objekte die Szene beeinflussen. Üblicherweise ist eine genaue Georeferenzierung der Daten notwendig um Konsistenz zwischen den einzelnen Modellen zu erreichen. Dies erhöht den Aufwand für die Datenakquise erheblich. In diesem Beitrag präsentieren wir robuste Verfahren zur vereinfachten Kombination unterschiedlicher Datensätze.

Andreas Nüchter, Jan Elseberg, and Dorit Borrmann. Optimale 3D-Punktwolken aus mobilen Laserscandaten. in Photogrammetrie Laserscanning Optische 3D-Messtechnik, Beiträge der Oldenburger 3D-Tage 2013, Jade Hochschule, Wichmann Verlag, February 2013.

Zusammenfassung: Mobiles Laserscanning stellt hohe Anforderungen an die Exaktheit der Positionierung und Kalibrierung des Messsystems, da sich bereits kleinste Ungenauigkeiten in den akquirierten 3D-Daten drastisch niederschlagen können. Dieser Beitrag präsentiert eine neuen Ansatz zur Kalibrierung und zur Lösung des SLAM-Problems mit dem Ziel, die Messgenauigkeit des mobilen Scansystems zu optimieren. Bei dem Kalibrierungsverfahren handelt es sich um eine allgemeingültige Methode, die die Positionierung und Orientierung sämtlicher Sensoren berechnet, einschließlich der Odometrie. Der vorgestellte SLAM-Ansatz (Simultaneous Localization and Mapping) ist semi-rigide. Dabei wird die Trajektorie so deformiert und jede Pose dahingehend optimiert, dass die Gesamtqualität der 3D-Punktwolke optimal wird. Das SLAM-Verfahren kann kurzfristige Sensorausfälle oder Ungenauigkeiten ausgleichen und ermöglicht vielfältige neue Anwendungen.

Remus-Claudiu Dumitru, Dorit Borrmann, and Andreas Nüchter. Interior Reconstruction using the 3D Hough Transform, In Proceedings of the 5th ISPRS International Workshop 3D-ARCH 2013: "3D Virtual Reconstruction and Visualization of Complex Architectures", Trento, Italy, February 2013. [Get Paper (PDF)] [Archive Link] .

Abstract: Laser scanners are often used to create accurate 3D models of buildings for civil engineering purposes, but the process of manually vectorizing a 3D point cloud is time consuming and error-prone (A. Adan and D. Huber). Therefore, the need to characterize and quantify complex environments automatically arises, posing challenges for data analysis. This paper presents a system for 3D modeling by detecting planes in 3D point clouds, based on which the scene is reconstructed at a high architectural level through removing automatically clutter and foreground data. The implemented software detects openings, such as windows and doors, and completes the architectural model by inpainting.

Mihai-Cotizo Sima and Andreas Nüchter. An extension of the Felzenszwalb-Huttenlocher segmentation to 3D point clouds, In Proceedings of the 5th International Conference on Machine Vision (ICMV '12), SPIE 8783, Wuhan, China, October 2012, DOI 10.1117/12.2010527, (878302 (March 13, 2013)), [Get Paper].

Abstract: This paper investigates the segmentation algorithm proposed by Felzenszwalb and Huttenlocher and its compatibility to 3D point clouds acquired with state-of-the-art 3D laser scanners. To use the algorithm, we adapt the range and intensity data to the smoothed graph structure used by the algorithm. We investigate the influence of the algorithm's parameters to its performance and result that are meaningful to both the machines and the humans.

Jan Elseberg, Dorit Borrmann, Andreas Nüchter. 6DOF Semi-Rigid SLAM for Mobile Scanning, In Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS '12), ISBN 978-1-4673-1735-1, pages 1865 - 1870, Vilamoura/Algarve, Portugal, October 2012, [Get Paper].

Abstract: The terrestrial acquisition of 3D point clouds by laser range finders has recently moved to mobile platforms. Measuring the environment while simultaneously moving the vehicle demands a high level of accuracy from positioning systems such as the IMU, GPS and odometry. We present a novel semi-rigid SLAM algorithm that corrects the global position of the vehicle at every point in time, while simultaneously improving the quality and accuracy of the entire acquired map. Using the algorithm the temporary failure of positioning systems or the lack thereof can be compensated for. We demonstrate the capabilities of our approach on a wide variety of systems and data sets.

Dorit Borrmann, Hassan Afzal, Jan Elseberg, Andreas Nüchter. Video: Thermal 3D Modeling of Indoor Environments for Saving Energy, In Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS '12), ISBN 978-1-4673-1735-1, pages 4538 - 4539, Vilamoura/Algarve, Portugal, October 2012, [Get Paper].

Abstract: Heat and air conditioning losses in buildings and factories lead to a large amount of wasted energy. The Action Plan for Energy Efficiency [COM241] of the European Commission estimates that the largest cost-effective energy savings potential lies in residential (27) and commercial (30%) buildings. Imagine a technology that creates a precise digital 3D model of heat distribution and heat flow enabling one to detect all sources of wasted energy and to modify buildings to reach these savings. This video presents our approach to this task. Methods for creating a consistent laser scan model enhanced with information from thermal and optical cameras are presented.

Dorit Borrmann, Andreas Nüchter, Marija Dakulovic, Ivan Maurovic, Ivan Petrovic, Dinko Osmankovic, and Jasmin Velagic. The Project ThermalMapper – Thermal 3D Mapping of Indoor Environments for Saving Energy. In Proceedings of the 10th International IFAC Symposium on Robot Control (SYROCO '12), Volume 10, Part 1, ISBN 978-3-902823-11-3, DOI 10.3182/20120905-3-HR-2030.00045, Dubrovnik, Croatia, September 2012, [Get Paper (PDF)].

Abstract: Heat and air conditioning losses in buildings and factories lead to a large amount of wasted energy. The Action Plan for Energy Efficiency of the [COM241] estimates that the largest cost-effective energy savings potential lies in residential (≈ 27%) and commercial (≈ 30%) buildings. Imagine a technology that creates a precise digital 3D model of heat distribution and heat flow enabling one to detect all sources of wasted energy and to modify buildings to reach these savings. This paper presents our overall approach to map indoor environments with thermal data in 3D.

Dorit Borrmann, Hassan Afzal, Jan Elseberg, and Andreas Nüchter. Mutual Calibration for 3D Thermal Mapping. In Proceedings of the 10th International IFAC Symposium on Robot Control (SYROCO '12), Volume 10, Part 1, ISBN 978-3-902823-11-3, DOI 10.3182/20120905-3-HR-2030.00073, Dubrovnik, Croatia, September 2012, [Get Paper (PDF)].

Abstract: Three-dimensional digital heat distribution maps are needed to assess the energy efficiency of real estates. The availability of such maps are of great importance for reducing the ecological footprint of houses, buildings, and factories. Designing estates has reached the point, where so-called Passivhaus buildings make extensive use of the intrinsic heat from internal sources such as waste heat from lighting, white goods, and other electrical devices, but without using dedicated heaters. In our approach for creating high-precise heat distribution maps a robot is equipped with a 3D laser scanner, a thermal camera, and a color camera. Data from all the sensors are combined to model the environment precisely. This paper describes the setup of the sensors and the processing of the acquired data, including the automatic co-calibration needed to fulfill this task.

Stefan May, Rainer Koch, Robert Scherlipp, and Andreas Nüchter. Robust Registration of Narrow-Field-of-View Range Images. In Proceedings of the 10th International IFAC Symposium on Robot Control (SYROCO '12), Volume 10, Part 1, ISBN 978-3-902823-11-3, DOI 10.3182/20120905-3-HR-2030.00057, Dubrovnik, Croatia, September 2012, [Get Paper (PDF)].

Abstract: This paper focuses on range image registration for robot localization and environment mapping. It extends the well-known Iterative Closest Point (ICP) algorithm in order to deal with erroneous measurements. The dealing with measurement errors originating from external lighting, occlusions or limitations in the measurement range is only rudimentary in literature. In this context we present a non-parametric extension to the ICP algorithm that is derived directly from measurement modalities of sensors in projective space. We show how aspects from reverse calibration can be embedded in search-tree-based approaches. Experiments demonstrate the applicability to range sensors like the Kinect device, Time-of-Flight cameras and 3D laser range nders. As a result the image registration becomes faster and more robust.

Mohammad Al-khawaldah and Andreas Nüchter. Multi-Robot Exploration and Mapping with a rotating 3D Scanner. In Proceedings of the 10th International IFAC Symposium on Robot Control (SYROCO '12), Volume 10, Part 1, ISBN 978-3-902823-11-3, DOI 10.3182/20120905-3-HR-2030.00025, Dubrovnik, Croatia, September 2012, [Get Paper (PDF)].

Abstract: This paper investigates the field of exploration and map-building with multiple cooperating mobile robots. New and efficient exploration and mapping technique is proposed by employing laser scanners. The paper also aims to extend existing exploration and mapping techniques of single robot to multi-robot to increase the exploration efficiency (i.e. to reduce the environment exploration time and the energy consumed by the robots to accomplish the exploration task). The goal of the proposed method is to have multiple mobile robots exploring a given unknown environment as fast as possible, while coordinating their actions and sharing their local maps in certain time instances. In the suggested technique, each robot is equipped with a laser scanner that is continuously rotating to scan the environment, and is employing a frontier-based exploration algorithm which is important to guide the robots during the exploration. A new factor is introduced to enhance the performance of the frontier-based exploration. This factor aims at spreading robots in the environment to reduce overlap.

Dorit Borrmann, Jan Elseberg, and Andreas Nüchter. Thermal 3D Mapping of Building Façades. In Proceedings of the 12th Conference on Intelligent Autonomous Systems (IAS '12), ISBN 978-3-642-33931-8, Jeju Island, Korea, June 2012, [Get Paper (PDF)].

Abstract: Never before in history were humans as dependant on energy as we are today. But the natural ressources are limited and a waste of energy has drastic influences on the environment. In their Action Plan for Energy Efficiency [COM241] the European Commission estimates that the largest and cost-effictive energy savings potential lies in residential (≈27%) and commercial (≈30%) buildings. To eliminate heat and air conditioning losses in buildings and factories heat and air leaks need to be localized and identified. Imagine the availability of a complete 3D model of every building that architects can use to analyze the heat insulation of buildings and to identify necessary modifications. In these 3D models temperature peaks are not only detectable but also their extent is visible. A robot equiped with a 3D laser scanner, a thermal camera, and a color camera constitutes the basis for our approach. The data from all three sensors and from different locations are joined into one high-precise 3D model that shows the heat distribution. This paper describes the setup of the hardware and the methods applied to create the 3D model, including the automatic co-calibration of the sensors. Challenges unique to the task of thermal mapping of outdoor environments are discussed.

Jan Elseberg, Dorit Borrmann, and Andreas Nüchter. Automatic and Full Calibration of Mobile Laser Scanning Systems. In Proceedings of the 13th International Symposium of Experimental Robotics (ISER '12), Springer Tracts in Advanced Robotics, Vol. 79, ISBN 978-3-642-28571-4, Québec City, Canada, June 2012.

Abstract: Mobile scanning, i.e., the practice of mounting laser scanners on moving platforms is an efficient way to acquire accurate and dense 3D point clouds of outdoor environments for urban and regional planning and architecture. The mobile scenario puts high requirements on the accuracy of the calibration of the measurement system, as small calibration inaccuracies lead to large errors in the resulting point cloud. We propose a novel algorithm for the calibration of a mobile scanning system that estimates the calibration parameters for \emph{all} sensor components simultaneously without relying on additional hardware. We evaluate the calibration algorithm on several real world data sets where ground truth is available via an accurate geodetic model.

Long Chen, Qingquan Li, Quanwen Zhu, Ming Li, and Andreas Nüchter. 3D LIDAR Point Cloud based Intersection Recognition for Autonomous Driving. In 2012 IEEE Intelligent Vehicles Symposium (IV '12), ISBN 978-1-4673-2118-1, pages 456-461, Alcalá de Henares, Madrid, Spain, June 2012. [Get Paper (PDF)].

Abstract: Finding road intersections in advance is crucial for navigation and path planning of moving autonomous vehicles, especially when there is no position or geographic auxiliary information available. In this paper, we investigate the use of a 3D point cloud based solution for intersection and road segment classification in front of an autonomous vehicle. It is based on the analysis of the features from the designed beam model. First, we build a grid map of the point cloud and clear the cells which belong to other vehicles. Then, the proposed beam model is applied with a specified distance in front of autonomous vehicle. A feature set based on the length distribution of the beam is extracted from the current frame and combined with a trained classifier to solve the road-type classification problem, i.e., segment and intersection. In addition, we also make the distinction between +-shaped and T-shaped intersections. The results are reported over a series of real-world data. A performance of above 80% correct classification is reported at a real-time classification rate of 5 Hz.

Ming Li, Wei Li, Jian Wang, Qingquan Li, and Andreas Nüchter Dynamic VeloSLAM – Preliminary Report on 3D Mapping of Dynamic Environments. In 2012 IEEE Intelligent Vehicles Symposium (IV '12), Workshop on Navigation, Perception, Accurate Positioning and Mapping for Intelligent Vehicles, Alcalá de Henares, Madrid, Spain, June 2012 [Get Paper (PDF)].

Abstract: 3D mapping using point cloud registration is a basic inevitable problem for many applications, especially for modeling of large scale complicated environments. This paper presents a novel approach for mapping highly dynamic environments, i.e., we present a system capable for mapping road traffic scenarios. Given 3D laser scans acquired at a high frame rate and no other sensor input, a 3D map is built by removing dynamic parts of the scene and estimating the ego-motion of the vehicle precisely at the same time. We extend the well-known ICP algorithm for HDL-64 laser scan data and build a system for solving the simultaneous localization and mapping problem in urban road scenarios. This paper presents initial results on two data sets.

Girum Demisse, Razvan Mihalyi, Billy Okal, Dev Poudel, Johannes Schauer, and Andreas Nüchter, Mixed Palletizing and Task Completion for Virtual Warehouses. in Virtual Manufacturing Automation (VMAC '12) Workshop at IEEE International Conference Robotics and Automation, ICRA, 2012 [Get Paper (PDF)].

Abstract: Palletizing, or packing rectangular boxes of various sizes onto pallets, is a frequently encountered task in many commercial scenarios, e.g., shipment of goods. An extension of this problem is the automated placement of boxes on pallets, henceforth task completion, by means of industrial robot arms. The palletizing and task completion problems are treated in the context of the IEEE ICRA 2012 Virtual Manufacturing Automation Competition. We approach the palletizing challenge by a winner-takes-all strategy, where multiple heuristics are evaluated against the given datasets. Our results show a performance comparable to that of the commercial software benchmark from the previous competitions. We solve task completion in USARSim by picking boxes and placing them on a pallet. Our inverse kinematics algorithm consists of a geometric and numeric component.

Thomas Wiemann, Kai Lingemann, Andreas Nüchter, and Joachim Hertzberg. A Toolkit for Automatic Generation of Polygonal Maps – Las Vegas Reconstruction. in Proceedings of the 7th German Conference Robotik 2012, pages 446-451, VDE Verlag, ISBN 978-3-8007-3418-4, Munich, Germany, May 2012. [Get Paper (PDF)].

Abstract: In this paper we present a new open source software package for automatic generation of polygonal 3D maps from point cloud data for robotic purposes called "Las Vegas Reconstruction Toolkit" [11]. The implemented algorithms focus on minimizing the computational costs and optimization of the number of polygons in the generated maps. Furthermore, we present two application examples: 6D self localization and scene interpretation.

Dorit Borrmann, Jan Elseberg, Prashant Narayan K.C., and Andreas Nüchter. Ein Punkt pro Kubikmeter – präzise Registrierung von terrestrischen Laserscans mit Scanmatching. in Photogrammetrie Laserscanning Optische 3D-Messtechnik, Beiträge der Oldenburger 3D-Tage 2012, pages 4-11, Jade Hochschule, Wichmann Verlag, ISBN 978-3-87907-515-7, February 2012.

Zusammenfassung: Die präzise Registrierung von terrestrischen Laserscans erfordert geschultes Personal, professionelle Scanner Hardware, meist proprietäre Software sowie genügend Zeit für die Anbringung von Zielmarken, Durchführung der Messungen und die anschlie&szilg;ende Verarbeitung der akquirierten Daten. Wir zeigen, wie man auf einige dieser Punkte verzichten und dennoch zu hochqualitativen Ergebnissen kommen kann.
Im Zuge einer Bachelorarbeit wurde ein der Vermessungstechnik fremder Informatikstudent damit beauftragt, den Campus der Jacobs University auf einer Teilfläche von ca. 9 ha zu vermessen. Zur Verfügung standen ein professioneller Scanner in Form des Riegl VZ-400. Insgesamt wurden 131 Aufnahmen mit insgesamt über 2 Milliarden Punkten gemacht. Nach manueller Vorregistrierung der Punktwolken erfolgte die präzise Anordnung dann vollautomatisch mit der frei erhältlichen Software 3DTK, die dazu in der Lage war die gesamte Datenmenge in kürzester Zeit mit höchster Genauigkeit zu registrieren.

Andreas Nüchter, HamidReza Houshiar, Dorit Borrmann, and Jan Elseberg. Projektionen für die Scanregistrierung mit Hilfe von Bildmerkmalen. in Photogrammetrie Laserscanning Optische 3D-Messtechnik, Beiträge der Oldenburger 3D-Tage 2012, pages 12-21, Jade Hochschule, Wichmann Verlag, ISBN 978-3-87907-515-7, February 2012.

Zusammenfassung: Die Aufnahme und das Registrieren von terrestrischen 3D-Laserscans ist eine grundlegende Fragestellung in vielen Anwendungsbereichen. Um den Prozess des Registrierens von zwei 3D-Scans zu automatisieren, werden Merkmale aus den Scandaten extrahiert, diese einander zugeordnet (assoziiert) und die Registrierung berechnet. Als Merkmale kommen neben Strukturmerkmalen wie 3D-Flächen oft Bildmerkmale zum Einsatz. Dazu wird ein flächiges Bild der Reflektionswerte eines 3D-Scans erzeugt. In der Regel wird hierbei auf der x-Achse der Rotationswinkel um die Stehachse des Scanners und auf der y-Achse der Rotationswinkel des Spiegels abgetragen. In diesem Beitrag untersuchen wir wie sich die Registrierungsergebnisse ändern, wenn andere Projektionen verwendet werden. Dazu analysieren wir mit Hilfe von SIFT-Merkmalen die gleichmäßige Rektangularprojektion, die zylindrische Projektion, die Hochachsenrojektion, die Mercatorprojektion, die Rektangularprojektion, die Pannini-Projektion, sowie die stereographische Projektion.

Flavia Grosan, Alexandru Tandrau, Andreas Nüchter. Localizing Google SketchUp Models in Outdoor 3D Scans. In Proceedings of the XXIII International Symposium on Information, Communication and Automation Technologies (ICAT '11), IEEE Xplore, ISBN 978-1-4577-0746-9, Sarajevo, Bosnia, October 2011 [Get Paper (PDF)] [Get Video] [Get Video].

Abstract: This work introduces a novel solution for localizing objects based on search strings and freely available Google SketchUp models. To this end we automatically download and preprocess a collection of 3D models to obtain equivalent point clouds. The outdoor scan is segmented into individual objects, which are sequentially matched with the models by a variant of iterative closest points algorithm using seven degrees of freedom and resulting in a highly precise pose estimation of the object. An error function evaluates the similarity level. The approach is verified using various segmented cars and their corresponding 3D models.

Jan Elseberg, Dorit Borrmann, and Andreas Nüchter. Full Wave Analysis in 3D Laser Scans for Vegetation Detection in Urban Environments. In Proceedings of the XXIII International Symposium on Information, Communication and Automation Technologies (ICAT '11), IEEE Xplore, ISBN 978-1-4577-0746-9, Sarajevo, Bosnia, October 2011, [Get Paper (PDF)].

Abstract: This paper presents a novel technique for detecting vegetation of virtually all forms in terrestrial laser scanning data of urban environments. We make use of a modern laser range finder capability to measure multiple echoes per laser pulse via Full Wave Analysis. The algorithm is able to efficiently, i.e., less than acquisition time, identify vegetation to a high degree of accuracy (more than 99 percent). We present and evaluate three alternatives to classify candidate regions as either vegetation or non-vegetation.

Jan Elseberg, Dorit Borrmann, and Andreas Nüchter. Efficient Processing of Large 3D Point Clouds. In Proceedings of the XXIII International Symposium on Information, Communication and Automation Technologies (ICAT '11), IEEE Xplore, ISBN 978-1-4577-0746-9, Sarajevo, Bosnia, October 2011, [Get Paper (PDF)].

Abstract: Autonomous robots equipped with laser scanners acquire data at an increasingly high rate. Registration, data abstraction and visualization of this data requires the processing of a massive amount of 3D data. The increasing sampling rates make it easy to acquire Billions of spatial data points. This paper presents algorithms and data structures for handling this data. We propose an efficient octree to store and compress 3D data without loss of precision. We demonstrate its usage for fast 3D scan matching and shape detection algorithms. We evaluate our approach using typical data acquired by mobile scanning platforms.

Andreas Nüchter, Seyedshams Feyzabadi, Deyuan Qiu, and Stefan May. SLAM à la carte - GPGPU for Globally Consistent Scan Matching. In Proceedings of the 4th European Conference on Mobile Robots (ECMR '11), Örebro, Sweden, September 2011 [Get Paper (PDF)].

Abstract: The computational complexity of SLAM is large and constitutes a challenge for real-time processing of a huge amount of sensor data with the limited resources of a mobile robot. Often, notebooks are used to control a mobile system and even these computing devices have nowadays graphics cards which allow general purpose computation using many cores. SLAM à la carte (graphique) exploits these capabilities and carries out 3D scan registrations on the GPU. A speed-up of more than one order of magnitude for precise 3D mapping is reported.

Andreas Nüchter, Stanislav Gutev, Dorit Borrmann, and Jan Elseberg. Skyline-based Registration of 3D Laser Scans. Proceedings of the Joint ISPRS workshop on 3D city modelling & applications and the 6th 3D GeoInfo (3DCMA '11), The Chinese Academic Journal (CD ROM version) CN 11-9251/G or ISSN 1671-6787, Wuhan, China, 2011, [Get Paper].

Abstract: Acquisition and registration of terrestrial 3D laser scans is a fundamental task in mapping and modeling of cities in three dimensions. To automate this task marker-free registration methods are required. Based on the existence of skyline features this paper proposes a novel method. The skyline features are extracted from panoramic 3D scans and encoded as strings enabling the use of string matching for merging the scans. Initial results of the proposed method in the old city center of Bremen are presented.

Jan Elseberg, Dorit Borrmann, and Andreas Nüchter. Eine effiziente Octree-Datenstruktur für das Verarbeiten von großen 3D-Punktwolken. in Photogrammetrie Laserscanning Optische 3D-Messtechnik, Beiträge der Oldenburger 3D-Tage 2011, Fachhochschule Oldenburg/Ostfr./Whv., ISBN 978-3-87907-506-5, pages 72-79, Wichmann Verlag, February 2011.

Zusammenfassung: Dieser Beitrag stellt eine neue Implementation der Octree-Datenstruktur vor, die es ermöglicht, eine Milliarde 3D-Punkte in 8 GB Hauptspeicher exakt zu repräsentieren und effiziente Algorithmen zu implementieren. Der Octree gibt eine Hierarchie vor, die dazu verwendet werden kann, große Punktewolken zu inspizieren und flüssig in ihnen zu navigieren.

Elena Digor, Andreas Birk, and Andreas Nüchter Exploration Strategies for a Robot with a Continously Rotating 3D Scanner, In Proceedings of the Second International Conference on Simulation, Modeling and Programming for Autonomous Robots (SIMPAR '10), Lecture Notes in Computer Science, Volume 6472/2010, ISBN-13 978-3-642-17318-9, pages 374-386, Darmstadt, Germany, November 2010, [Get Paper] [Get Video 1 (MPEG)] [Get Video 1 (MPEG)].

Abstract: To benchmark the efficiency of exploration strategies one has to use robot simulators. In an exploration task, the robot faces an unknown environment. Of course one could test the algorithm in different real-world scenarios, but a competitive strategy must have good performance in any environment that can be systematically constructed inside a simulator. This paper presents an evaluation of exploration strategies we developed for a specific sensor. A continously rotating 3D laser scanner that scans only into one direction at a time moves through the environment sampling the surrounding. Our evaluation framework features an efficient scanning and robot simulator for kinematic feasible trajectories. We will show that shorter trajectories do not necessarily imply quicker exploration. A simple simulator framework is sufficient for evaluating these properties of path planning algorithms.

Jan Elseberg, Dorit Borrmann, Andreas Nüchter, and Kai Lingemann. Non-Rigid Registration and Rectification of 3D Laser Scans, In Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS '10), ISBN 978-1-4244-6676-4, pages 1546-1552, Taipei, Taiwan, October 2010, [Get Paper].

Abstract: Three dimensional point clouds acquired by range scanners often do not represent the environment precisely due to noise and errors in the acquisition process. These latter systematical errors manifest as deformations of different kinds in the 3D range image. This paper presents a novel approach to correct deformations by an analysis of the structures present in the environment and correcting them by non-rigid transformations. The resulting algorithms are used for creating high-accuracy 3D indoor maps.

Kaustubh Pathak, Dorit Borrmann, Jan Elseberg, Narunas Vaskevicius, Andreas Birk, Andreas Nüchter. Evaluation of the Robustness of Planar-Patches based 3D-Registration using Marker-based Ground-Truth in an Outdoor Urban Scenario, In Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS '10), ISBN 978-1-4244-6676-4, pages 5725-5730, Taipei, Taiwan, October 2010, [Get Paper].

Abstract: The recently introduced Minimum Uncertainty Maximum Consensus (MUMC) algorithm for 3D scene registration using planar-patches is tested in a large outdoor urban setting without any prior motion estimate whatsoever. With the aid of a new overlap metric based on unmatched patches, the algorithm is shown to work successfully in most cases. The absolute accuracy of its computed result is corroborated for the first time by ground-truth obtained using reflective markers. There were a couple of unsuccessful scan-pairs. These are analyzed for the reason of failure by formulating two kinds of overlap metrics: one based on the actual overlapping surfacearea and another based on the extent of agreement of rangeimage pixels.We conclude that neither metric in isolation is able to predict all failures, but that both taken together are able to predict the difficulty level of a scan-pair vis-a-vis registration by MUMC.

Dorit Borrmann, Jan Elseberg, Shaan S. Rauniyar, and Andreas Nüchter. Lifelong 3D Mapping – Monitoring with a 3D Scanner, In Proceedings of the IEEE/RSJ IROS Workshop on Robotics for Environmental Monitoring, Taipei, Taiwan, October 2010. [Get Paper]. [Note: This workshop was canceled, but the organizers decided to publish all reviewed and accepted papers online. Please use this link to visit the workshop webpage.

Abstract: Geodesy and surveying are the sciences for monitoring the earth. In recent years traditional surveying equipment has been pushed aside by the emerging technology of laser scanners, that automate the precise measurement of points in the environment. A further step of automation is achieved by operating the surveying equipment automatically and the usage of robotic mapping. Thus, robotic mapping will become a key component in monitoring and surveillance tasks. This paper evaluates a 3D laser scanner from surveying for its usage in robotic monitoring tasks. We examine how seasonal changes and weather conditions impact the data of the 3D scanner and how to deal with these changes. For this analysis 3D scans of various predetermined locations on the campus of the Jacobs University Bremen were taken on a weekly basis over a period of 13 weeks using the RIEGL VZ-400 3D laser range finder. The scans have been registered by means of conventional surveying markers, SIFT features and using our point cloud based 6D SLAM framework. An analysis of the changes in the environment over the course of the scanning period and an evaluation of the matching results complete the analysis.

Dorit Borrmann, Jan Elseberg, Kai Lingemann, and Andreas Nüchter. A Data Structure for the 3D Hough Transform for Plane Detection, in Proceedings of the 5th IFAC Symposium on Intelligent Autonomous Vehicles (IAV '10), Lecce, Italy, September 2010, [Get Paper].

Abstract: The Hough Transform is a well-known method for detecting parametrized objects. It is the de facto standard for the detection of lines and circles in 2-dimensional data sets. For 3D it has attained little attention so far. Apart from computational costs, the main problem is the representation of the accumulator: Usual implementations favor geometrical objects with certain parameters due to uneven sampling of the parameter space. In this paper we present a novel approach to design the accumulator focusing on achieving the same size for each cell. The proposed accumulator is compared to previously known designs.

Jan Wülfing, Joachim Hertzberg, Kai Lingemann, Andreas Nüchter, Thomas Wiemann, and Stefan Stiene. Towards Real Time Robot 6D Localization in a Polygonal Indoor Map Based on 3D ToF Camera Data, in Proceedings of the 5th IFAC Symposium on Intelligent Autonomous Vehicles (IAV '10), Lecce, Italy, September 2010, [Get Paper].

Abstract: This paper reports a method and results for solving the following problem: Given a 3D polygonal indoor map and a mobile robot equipped with a 3D time of flight (ToF) camera, localize at frame rate the 6D robot pose with respect to the map. To solve the problem, the polygonal map is represented for efficient usage as a solid-leaf BSP tree; at each control cycle, the 6D pose change is estimated a priori from odometry or IMU, the expected ToF camera view at the prior pose sampled from the BSP tree, and the pose change estimation corrected a posteriori by fast ICP matching of the expected and the measured ToF image. Our experiments indicate that, first, the method is in fact real-time capable; second, the 6D pose is tracked reliably in a correct map under regular sensor conditions; and third, the tracking can recover from some faults induced by local map inaccuracies and transient or local sensing errors.

Thomas Wiemann, Andreas Nüchter, Kai Lingemann, Stefan Stiene and Joachim Hertzberg. Automatic Construction of Polygonal Maps From Point Cloud Data, in Proceedings of the International Workshop on Safty, Security and Rescue Robotics (SSRR '10), Bremen, Germany, July 2010, [Get Paper].

Abstract: This paper presents a novel approach to create polygonal maps from 3D point cloud data. The gained map is augmented with a interpretation of the scene. Our procedure shows to be fast and reliable and produces accurate maps in indoor environments. The created maps are used with different kinds of sensors for reliable self localization.

Andreas Nüchter, Jan Elseberg, Peter Schneider, and Dietrich Paulus. Linearization of Rotations for Globally Consistent n-Scan Matching, in Proceedings of the IEEE International Conference Robotics and Automation (ICRA '10), ISBN 978-1-4244-5040-4, pages 1373-1379, Anchorage, Alaska, May 2010, [Get Paper (PDF)].

Abstract: The ICP (Iterative Closest Point) algorithm is the de facto standard for geometric alignment of three-dimensional models when an initial relative pose estimate is available. The basis of the algorithm is the minimization of an error function that takes point correspondences into account. While four closed-form solution methods are known for minimizing this function, linearization seems necessary for solving the global scan registration problem. This paper presents such linear solutions for registering n-scans in a global and simultaneous fashion. It studies parameterizations for the rigid body transformations of the n-scan registration problem.

Dorit Borrmann, Jan Elseberg, Kai Lingemann, and Andreas Nüchter. Verbesserte Kartenqualität durch Thin Plate Splines und Hough-Transformation. in Photogrammetrie Laserscanning Optische 3D-Messtechnik, Beiträge der Oldenburger 3D-Tage 2010, Fachhochschule Oldenburg/Ostfr./Whv., ISBN 978-3-87907-494-5, pages 134-141, Wichmann Verlag, February 2010.

Abstract: Laserscanner sind präzise Messgeräte zur Ermittlung von Distanzwerten. Dennoch weist eine jede mit einem Laserscanner akquirierte Punktwolke Fehler auf, die auch durch Kalibrierung nicht vollständig verhindert werden können. Neben Sensorrauschen kommt es auch zu systematischen Fehlern. Die meisten künstlich geschaffenen Umgebungen bestehen aus einer großen Anzahl ebener Flächen, die helfen können, die Qualität von Laserscan-Karten zu verbessern. Dieser Aufsatz stellt Methoden vor, die unter Zuhilfenahme von ebenen Umgebungsstrukturen die Fehler in den Laserscans durch nicht-rigide Verformungen verringern.

Andreas Nüchter. 6D SLAM mit Global Konsistentem Scanmatching, In Terrestrisches Laserscanning (TLS 2009) Beiträge zum 91. DVW-Seminar am 18. und 19. November in Fulda, (invited paper), ISBN 978-3-89639-734-8, pages 69-92, Fulda, Germany, November 2009.

Einleitung: Terrestrisches Laserscanning (TLS) hat die in den letzten Jahren die Vermessungstechnik revolutioniert. Durch die Entwicklung des kinematischen terrestrischen Laserscannings (k-TLS) oder Mobile Mapping, das die Aufnahme von geometrische Umgebungsinformation von einer bewegten Plattform aus erlaubt, wurde ein wesentlicher Schritt zur weiteren Automatisierung in der Vermessungstechnik getan. Leider ist k-TLS nicht überall einsetzbar, da neben den Daten des Laserscanners hochgenaue Informationen über die Pose (Position und Orientierung) der mobilen Plattform vorliegen müssen.
Technischer Fortschritt erlaubt den Bau von autonomen Robotersystemen, die mit 3D-Laserscannern ausgestattet sind und es besteht Potential für weitere Automatisierung. Dazu muss das Problem der gleichzeitigen Lokalisation und Kartierung gelöst werden. Dieses klassische Robotikproblem ist ein Henne-und-Ei-Problem: Mit genauster Kenntnis der Position des mobilen Roboters lassen sich korrekte Karten erzeugen. Mit Hilfe von Karten können sich Roboter sehr genau lokalisieren. Beides gleichzeitig durchzuführen stellt neue hohe Anforderungen an die Algorithmen, die Scannerdaten verarbeiten.
...

Deyuan Qiu, Stefan May, and Andreas Nüchter. GPU-accelerated Nearest Neighbor Search for 3D Registration. In Proceedings of the 7th International Conference on Computer Vision Systems (ICVS '09). LNCS 5815, Spinger ISBN 978-3-642-04666-7, pages 194-203, Lìege Belgium, October 2009. [Get Paper (PDF)]

Nearest Neighbor Search (NNS) is employed by many computer vision algorithms. The computational complexity is large and constitutes a challenge for real-time capability. The basic problem is in rapidly processing a huge amount of data, which is often addressed by means of highly sophisticated search methods and parallelism. We show that NNS based vision algorithms like the Iterative Closest Points algorithm (ICP) can achieve real-time capability while preserving compact size and moderate energy consumption as it is needed in robotics and many other domains. The approach exploits the concept of general purpose computation on graphics processing units (GPGPU) and is compared to parallel processing on CPU. We apply this approach to the 3D scan registration problem, for which a speed-up factor of 88 compared to a sequential CPU implementation is reported.

Jochen Sprickerhof, Andreas Nüchter, Kai Lingemann, Joachim Hertzberg. An Explicit Loop Closing Technique for 6D SLAM, In Proceedings of the 4th European Conference on Mobile Robots (ECMR '09), Mlini/Dubrovnic, Croatia, September 2009. [ Get Paper (PDF)] [Get Videos].

Abstract: Simultaneous Localization and Mapping (SLAM) is the problem of building a map of an unknown environment by a mobile robot while at the same time navigating the environment, using the unfinished map. For SLAM, two tasks have to be solved: First reliable feature extraction and data association, second the optimal estimation of poses and features. These two parts are often referred to as SLAM frontend and backend. Algorithms that solve SLAM by using laser scans commonly rely on matching closest points in the frontend part. Then the SLAM front- and backend have to be iterated to ensure that the map converges.
This paper presents a novel approach for solving SLAM using 3D laser range scans. We aim at avoiding the iteration between the SLAM front- and backend and propose a novel explicit loop closing heuristic (ELCH). It dissociates the last scan of a sequence of acquired scans, reassociates it to the map, built so far by scan registration, and distributes the difference in the pose error over the SLAM graph. We describe ELCH in the context of SLAM with 3D scans considering 6 DoF. The performance is evaluated using ground truth data of an urban environment.

Stefan May, David Dröschel, Dirk Holz, Stefan Fuchs, Andreas Nüchter. Robust 3D-Mapping with Time-of-Flight Cameras, In Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS '09), ISBN 978-1-4244-3804-4, St. Louis, MO, USA, October 2009.

Abstract: Time-of-Flight cameras constitute a smart and fast technology for 3D robotic perception but lack in measurement precision and robustness. We present a comprehensive approach for 3D environment mapping based on this technology. Imprecision of depth measurements are properly handled by calibration and application of several filters. Robust registration is performed by a novel extension to the Iterative Closest Point algorithm. Remaining registration errors are refined by global relaxation after loop-closure and surface smoothing. A laboratory ground truth evaluation is provided as well as 3D mapping experiments in a larger indoor environment.

Martin Magnusson, Henrik Andreasson, Andreas Nüchter, Achim J. Lilienthal. Appearance-Based Place Recognition from 3D Laser Data Using the Normal Distributions Transform, in Proceedings of the IEEE International Conference Robotics and Automation (ICRA '09), ISBN 987-1-4244-2789-5, pages 23 - 28, Kobe, Japan, May 2009 [Get Paper (PDF)].

Abstract: To advance robotic science it is important to perform experiments that can be replicated by other researchers to compare different methods. However, these comparisons tend to be biased, since re-implementations of reference methods often lack thoroughness and do not include the hands-on experiences obtained during the original development process. This paper presents the results of a field experiment, carried out by two research groups that are leading in the field of 3D robotic mapping. The iterative closest points algorithm (ICP) is compared to the normal distributions transform (NDT).
We also present an improved version of NDT with a substantially larger valley of convergence than previously published versions.

Martin Magnusson, Andreas Nüchter, Christopher Lörken, Achim, J. Lilienthal, and Joachim Hertzberg. Evaluation of 3D Registration Reliability and Speed – A Comparison of ICP and NDT in Proceedings of the IEEE International Conference Robotics and Automation (ICRA '09), ISBN 987-1-4244-2789-5, pages 3907 - 3912, Kobe, Japan, May 2009 [Get Paper (PDF)].

Abstract: We propose a new approach to appearance based place recognition from metric 3D maps, exploiting the NDT surface representation. Locations are described with feature histograms based on surface orientation and smoothness, and loop closure can be detected by matching feature histograms.
We also present a quantitative performance evaluation using two real-world data sets, one of which is highly self-similar, showing that the proposed method works well in different environments.

Andreas Nüchter and Jan Elseberg. Linearisierte Lösung der ICP-Fehlerfunktion für global konsistentes Scanmatching. in Photogrammetrie Laserscanning Optische 3D-Messtechnik, Beiträge der Oldenburger 3D-Tage 2009, Fachhochschule Oldenburg/Ostfr./Whv., ISBN 978-3-87907-478-5, Wichmann Verlag, pages 74 - 81, 2009.

Zusammenfassung: Dieser Artikel beschreibt eine Linearisierung in geschlossener Form für die Minimierung der Fehlerfunktion, die beim ICP-Algorithmus auftaucht. Die Linearisierung approximiert die tatsächliche Lösung und nutzt die Annahme aus, dass die auftretenden Winkel klein sind. Weiterhin zeigt der Artikel die Möglichkeit auf, die Linearisierung für global konsistentes Scanmatching zu verwenden. Global konsistentes Scanmatching minimiert den Gesamtfehler, wenn mehr als zwei 3D-Punktwolken vorliegen.

Andreas Nüchter, Kai Lingemann, and Joachim Hertzberg. Evaluating a 3D Camera for RoboCup Rescue. In Proceedings of the SICE Annual Conference 2008: International Conference on Instrumentation, Control and Information Technology (SICE '08), ISBN 978-4-907764-29-6, pp. 2070-2075, Tokyo, Japan, August, 2008.

Abstract: The following paper evaluates a time-of-flight 3D camera with regards to its usability for RoboCup Rescue. This includes an evaluation of the influence of outer conditions to the camera data, as well as its usage for automatic 3D mapping by scan registration. A color camera is calibrated with respect to the 3D camera in order to gain colored texture information for the acquired measurements.

Dorit Borrmann, Jan Elseberg, Kai Lingemann, Andreas Nüchter, and Joachim Hertzberg. The Efficient Extension of Globally Consistent Scan Matching to 6 DoF. In Proceedings of the 4th International Symposium on 3D Data Processing, Visualization and Transmission (3DPVT '08), Available electronically as Tech Report GT-IC-08-05 from the Georgia Institute of Technology, Atlanta, GA, USA, pages 29-36, June 2008 [Get Paper] [Get Video] [Addendum].

Abstract: Over ten years ago, Lu and Milios presented a probabilistic scan matching algorithm for solving the simultaneous localization and mapping (SLAM) problem with 2D laser range scans, a standard in robotics. This paper presents an extension to this GraphSLAM method. Our iterative algorithm uses a sparse network to represent the relations between several overlapping 3D scans, computes in every step the 6 degrees of freedom (DoF) transformation in closed form and exploits efficient data association with cached k-d trees. Our approach leads to globally consistent 3D maps, precise 6D pose and covariance estimates, as demonstrated by various experimental results.

Andreas Nüchter, Kai Lingemann, Dorit Bormann, Jan Elseberg, and Jan Böhm. Global Konsistente 3D-Kartierung mit Scanmatching. in Photogrammetrie Laserscanning Optische 3D-Messtechnik, Beiträge der Oldenburger 3D-Tage 2008, Fachhochschule Oldenburg/Ostfr./Whv. ISBN 978-3-87907-463-1, Wichmann Verlag, pages 194 - 201, February 2008.

Abstract: Das Einpassen bzw. Registrieren von Punktmengen unter starren Transformationen ist eines der Grundprobleme in der Bildverarbeitung. Hierbei können die 3D-Daten aus Laserscannern, Stereokameras u.ä. stammen. Für zwei 3D-Punktmengen bildet der ICP-Algorithmus (Iterative Closest Points) einen de facto Standard für das Registrieren. Weitet man diesen Algorithmus jedoch auf viele 3D-Scans aus, akkumulieren sich Registrierungsfehler. Der vorliegende Beitrag skizziert einen neuen Algorithmus für das global konsistente 3D-Scanmatching (Borrmann, Elseberg, Lingemann, Nüchter und Hertzberg 2008) und zeigt eine Anwendung für das Erfassen von Gebäuden. Die Genauigkeit des Algorithmus wird bezüglich geodätischer Methoden evaluiert.

Oliver Wulf, Andreas Nüchter, Joachim Hertzberg, and Bernardo Wagner. Ground Truth Evaluation of Large Urban 6D SLAM. In Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS '07), pages 650 - 657, ISBN 1-4244-0912-8, San Diego, CA, USA, October - November, 2007 [Get Paper]. [Get Videos]

Abstract: In the past many solutions for simultaneous localization and mapping (SLAM) have been presented. Recently these solutions have been extended to map large environments with six degrees of freedom (DoF) poses. To demonstrate the capabilities of these SLAM algorithms it is common practice to present the generated maps and successful loop closing. Unfortunately there is often no objective performance metric that allows to compare different approaches. This fact is attributed to the lack of ground truth data. For this reason we present a novel method that is able to generate this ground truth data based on reference maps. Further on, the resulting reference path is used to measure the absolute performance of different 6D SLAM algorithms building a large urban outdoor map.

Andreas Nüchter. Parallelization of Scan Matching for Robotic 3D Mapping. In Proceedings of the 3rd European Conference on Mobile Robots (ECMR '07), Freiburg, Germany, September 2007, [Get Paper], [View Online Proceedings].

Abstract: Robotic 3D Mapping of environments is computationally expensive, since 3D scanners sample the environment with many data points. In addition, the solution space grows exponentially with the additional degrees of freedom needed to represent the robot pose. Mapping environments in 3D must regard six degrees of freedom to characterize the robot pose. This paper extends our solution to the 3D mapping problem by parallelization. The availability of multi-core processors as well as efficient programming schemes as OpenMP permit the parallel execution of robotics task with on-board means.

Andreas Bartel, Frank Meyer, Christopher Sinke, Thomas Wiemann, Andreas Nüchter, Kai Lingemann, and Joachim Hertzberg. Real-Time Outdoor Trail Detection on a Mobile Robot. In Proceedings of the 13th IASTED International Conference on Robotics and Applications, ISBN 978-0-88986-686-7, pages 477 - 482, Würzburg, Germany, August 2007, [Get Paper and Videos].

Abstract: In this paper we present a reliable approach for real-time outdoor trail following and obstacle avoidance. The trail classification is done using an off-the-shelf webcam and a pitched 2D laser scanner on a KURT2 robot equipped with an Intel Centrino laptop. This simple setup enables us to follow given pathways of different kinds using a GPS receiver for rough orientation.

Andreas Nüchter, Kai Lingemann, and Joachim Hertzberg. 6D SLAM with Cached k-d tree Search. In Proceedings of the 13th IASTED International Conference on Robotics and Applications, ISBN 978-0-88986-686-7, pages 181 - 186, Würzburg, Germany, August 2007.

Abstract: 6D SLAM (Simultaneous Localization and Mapping) or 6D Concurrent Localization and Mapping of mobile robots considers six degrees of freedom for the robot pose, namely, the x, y and z coordinates and the roll, yaw and pitch angles. In previous work we presented our scan matching based 6D SLAM approach [cite deleted], where scan matching is based on the well known iter ative closest point (ICP) algorithm [3]. Effcient implementations of this algorithm are a result of a fast computation of closest points. The usual approach, i.e., using k-d trees is extended in this paper. We describe a novel search strategy, that lead s to significant speed-ups. Our mapping system is real-time capable, i.e., 3D maps are computed using the resources of the used robotic hardware.

Rolf Lakaemper, Andreas Nüchter, Nagesh Adluru, and Longin Jan Latecki. Performance of 6D LuM and FFS SLAM - An Example for Comparison using Grid and Pose Based Evaluation Methods. In Proceedings of seventh workshop on Performance Metrics for Intelligent Systems (PerMIS '07), Washington D.C., USA, August 2007, [Get Paper (PDF)].

Abstract: The focus of this paper is on the performance comparison of two simultaneous localization and mapping (SLAM) algorithms namely 6D Lu/Milios SLAM and Force Field Simulation (FFS). The two algorithms are applied to a 2D data set. Although the algorithms generate overall visually comparable results, they show strengths and weaknesses in different regions of the generated global maps. The question we address in this paper is, if different ways of evaluating the performance of SLAM algorithms project different strengths and how can the evaluations be useful in selecting an algorithm. We will compare the performance of the algorithms in different ways, using grid and pose based quality measures.

Andreas Nüchter, Kai Lingemann, and Joachim Hertzberg. Cached k-d tree search for ICP algorithms. In Proceedings of the 6th IEEE International Conference on Recent Advances in 3D Digital Imaging and Modeling (3DIM '07), IEEE Computer Society Press, ISBN 0-7695-2939-9, pages 419 - 426, Montreal, Canada, August 2007, [Get Paper (PDF)] [HTML Version].

Abstract: The ICP (Iterative Closest Point) algorithm is the de facto standard for geometric alignment of three-dimensional models when an initial relative pose estimate is available. The basis of ICP is the search for closest points. Since the development of ICP, k-d trees have been used to accelerate the search. This paper presents a novel search procedure, namely cached k-d trees, exploiting iterative behavior of the ICP algorithm. It results in a significant speed-up of about 50% as we show in an evaluation using different data sets.

Giovanni Indiveri, Andreas Nüchter, and Kai Lingemann. High Speed Differential Drive Mobile Robot Path Following Control With Bounded Wheel Speed Commands, in Proceedings of the IEEE International Conference Robotics and Automation (ICRA '07), ISBN 1-4244-0602-1, pages 2202 - 2207, Rome, Italy, April 2007, [Get Paper (PDF)].

Abstract: The great majority of path following control laws for either kinematical or dynamical mobile robot models are designe d assuming ideal actuators, i.e. assuming that any commanded velocity or torque (in the kinematical and dynamical ca ses respectively) will be instantly implemented regardless of its value. Real actuators are far from being ideal. In particular, only bounded velocities and torques can be realized for any given command. With reference to the kinemati cal model of a differential drive mobile robot, a known path following control law is modified to account for actuator velocity saturation. The proposed solution is experimentally shown to be particularly useful for high speed applica tions where accounting for actuator velocity saturation may have a large influence on performance.

Lars Kunze, Kai Lingemann, Andreas Nüchter, and Joachim Hertzberg. Salient Visual Features to Help Close the Loop in 6D SLAM, in Proceedings of the ICVS Workshop on Computational Attention & Applications (WCAA '07), Bielefeld, Germany, ISBN 978-3-00-020933-8, March 2007, [Get Paper (PDF)].

Abstract: One fundamental problem in mobile robotics research is Simultaneous Localization and Mapping (SLAM): A mobile robot has to localize itself in an unknown environment, and at the same time generate a map of the surrounding area. One fundamental part of SLAM algorithms is loop closing: The robot detects whether it has reached an area that has been visited before, and uses this information to improve the pose estimate in the next step. In this work, visual camera features are used to assist closing the loop in an existing 6 degree of freedom SLAM (6D SLAM) architecture. For our robotics application we propose and evaluate several detection methods, including salient region detection and maximally stable extremal region detection. The detected regions are encoded using SIFT descriptors and stored in a database. Loops are detected by matching of the images' descriptors. A comparison of the different feature detection methods shows that the combination of salient and maximally stable extremal regions suggested by performs moderately.

Andreas Nüchter. Algorithmen zur Erstellung virtueller 3D-Welten mit mobilen Robotern, in Photogrammetrie Laserscanning Optische 3D-Messtechnik, Beiträge der Oldenburger 3D-Tage 2007, Fachhochschule Oldenburg/Ostfr./Whv, ISBN 978-3-87907-447-1, Wichmann Verlag, pages 164 - 171, February 2007.

Zusammenfassung: 3D-Laserscanner sind eine junge Technologie, die die Erfassung räumlicher Daten revolutioniert und Robotern das dreid imensionale Abtasten von Objekten möglich macht. Roboter, die ihre Umgebung dreidimensional kartieren können, eignen sich zum automatischen Erstellen virtuelle 3D-Welten. Eine 3D-Welt, oder 3D-Umgebungskarte muss mit der wirklichen Umgebung übereinstimmen, also korrekt und konsistent sein. Ist die Position des Roboters genau bekannt, können die loka len Karten auf der Grundlage dieser Position zusammengefügt werden. Leider ist die Selbstlokalisation eines Roboters stets fehlerbehaftet. Daher darf der Kartenbau nicht nur auf der Roboterposition basieren, sondern muss auch auf der Grundlage der Sensorwerte geschehen. In diesem Zusammenhang spricht man vom simultanen Lokalisations- und Kartierungs problem (SLAM, simultaneous localization and mapping problem). Korrekte, global konsistente Modelle entstehen durch e inen 6D-SLAM Algorithmus. Hierbei werden 6 Freiheitsgrade in der Roboterpose berücksichtigt, geschlossene Kreise erka nnt und der globale Fehler minimiert. Die Basis des 6D-SLAM ist ein sehr schneller ICP-Algorithmus.

Andreas Nüchter, Kai Lingemann and Joachim Hertzberg. 6D SLAM with Kurt3D, in Robotic 3D Environment Cognition, Workshop at the International Conference Spatial Cognition, Bremen, Germany 2006. [Get Paper (PDF)]

Abstract: 6D SLAM (Simultaneous Localization and Mapping) or 6D Concurrent Localization and Mapping of mobile robots considers six dimensions for the robot pose, namely, the x, y and z coordinates and the roll, yaw and pitch angles. Robot motion and localization on natural surfaces, e.g., when driving with a mobile robot outdoor, must regard these degrees of freedom. 3D (6 DOF) scan matching, combined with a heuristic for closed loop detection and a global relaxation method, results in a highly precise mapping system for outdoor environments. The mobile robot Kurt3D is capable to run the mapping process with its on-board sensors and computers and is used to digitalize different environments. This paper summarizes our previous research.

Andreas Nüchter, Kai Lingemann, Joachim Hertzberg, and Hartmut Surmann. 6D SLAM – Mapping Outdoor Environments, in Proceedings of the International Workshop on Safty, Security and Rescue Robotics (SSRR '06), (CDROM Proceedings), Gaithersburg, Maryland, USA, August 2006,

Abstract: 6D SLAM (Simultaneous Localization and Mapping) of mobile robots considers six dimensions for the robot pose, namely, the x, y and z coordinates and the roll, yaw and pitch angles. Robot motion and localization on natural surfaces, e.g., when driving with a mobile robot outdoor, must regard these degrees of freedom. This paper presents a robotic mapping method based on locally consistent 3D laser range scans. Scan matching, combined with a heuristic for closed loop detection and a global relaxation method, results in a highly precise mapping system for outdoor environments. The mobile robot Kurt3D was used to acquire data of the Schloss Birlinghoven campus. The resulting 3D map is compared with ground truth, given by an aerial photograph.

Sven Albrecht, Joachim Hertzberg, Kai Lingemann, Andreas Nüchter, Jochen Sprickerhof, Stefan Stiene. Device Level Simulation of Kurt3D Rescue Robots, in Third International Workshop on Synthetic Simulation and Robotics to Mitigate Earthquake Disaster (SRMED 2006). CDROM Proceedings, June 2006 [Get Paper (PDF)] [Get Paper (HTML)].

Abstract: USARSIM is a worldwide used robot simulator deployed in Urban Search and Rescue (USAR) and in the context of the RoboCup Rescue Real Robot contest. This paper describes the USARSIM simulator for KURT2 and Kurt3D robot platforms, which we are using in both education and research. As it simulates on the device level, a seamless integration of real robot control software with the simulations becomes possible. We evaluate the performance for simulating laser range scans and the camera system. In addition, we show a simulation of the rescue robots.

Stefan Stiene, Kai Lingemann, Andreas Nüchter, and Joachim Hertzberg. Contour-based Object Detection in Range Images, in Proceedings of the Third International Symposium on 3D Data Processing, Visualization and Transmission (3DPVT '06), CDROM Proceedings, June 2006. [Get Paper (PDF)]

Abstract: This paper presents a novel object recognition approach based on range images. Due to its insensitivity to illumination, range data is well suited for reliable silhouette extraction. Silhouette or contour descriptions are good sources of information for object recognition. We propose a complete object recognition system, based on a 3D laser scanner, reliable contour extraction with floor interpretation, feature extraction using a new, fast Eigen-CSS method, and a supervised learning algorithm. The recognition system was successfully tested on range images acquired with a mobile robot, and the results are compared to standard techniques, i.e., Geometric features, Hu and Zernike moments, the Border Signature method and the Angular Radial Transformation. An evaluation using the receiver operating characteristic analysis completes this paper. The Eigen-CSS method has proved to be comparable in detection performance to the top competitors, yet faster than the best one by an order of magnitude in feature extraction time.

Andreas Nüchter, Kai Lingemann, and Joachim Hertzberg. Extracting Drivable Surfaces in Outdoor 6D SLAM, in Proceedings of the 37nd International Symposium on Robotics (ISR '06) and 4th German Conference Robotik 2006, ISBN 3-18-091956-6, Munich, Germany, 2006. [Get Paper (PDF)] [Get Paper (HTML)] [Get Surface Animation (DivX)] [Get Marching Cubes Representation (DivX)]

Abstract: A basic issue of mobile robotics is generating environment maps automatically. Outdoor terrain is challenging since the ground is uneven and the surrounding is structured irregularly. In earlier work, we have introduced 6D SLAM (Simultaneous Localization and Mapping) as a method to taking all six DOF of robot poses (x, y, z translation; roll, pitch, yaw angles) into account. This paper adds to 6D SLAM a method for extracting drivable surfaces in the 3D maps while they are being generated. Experiments have been made in a Botanical Garden, with drivable surfaces consisting of gravel paths or lawn, both involving significant slope.

Kai Lingemann, Andreas Nüchter, Joachim Hertzberg, and Hartmut Surmann. About the Control of High Speed Mobile Indoor Robots, in Proceedings of the Second European Conference on Mobile Robotics (ECMR '05), ISBN 88-89177-187, Ancona, Italy, September 2005, pages 218 - 223. [Get Paper and Video]

Abstract: This paper describes the control algorithms of the high speed mobile robot Kurt3D. Kurt3D drives up to 4 m/s autonomously and reliably in an unknown office environment. We present the reliable hardware, fast control cycle algorithms and a novel set value computation scheme for achieving these velocities. In addition we sketch a real-time capable laser based position tracking method that is well suited for driving with these velocities.

Joachim Hertzberg, Kai Lingemann, and Andreas Nüchter. USARSIM – Game-Engines in der Robotik-Lehre, in A. B. Cremers et al. (eds.): Informatik 2005 – Informatik LIVE, vol.1 (Beiträge der 35. Jahrestagung der Gesellschaft für Informatik, Bonn). ISBN 3-88579-396-2, pages 158-162 Gesellschaft für Informatik, Bonn, Germany, September 2005. [Get Paper (PDF)].

Abstract: In der Lehre zum Thema Wissensbasierte Robotik verwenden wir seit Kurzem den Robotersimulator USARSIM, der weltweit im Kontext der RoboCup Rescue Real Robot Liga eingesetzt wird. Wir stellen den Lehr-Kontext vor, in dem wir arbeiten, skizzieren den Simulator und beschreiben seine Einbindung in unsere Lehre. Unsere Erfahrungen bezuglich der Motivation der Studierenden und ihrer Leistungen der Verwendung des Simulators sind sehr positiv.

Andreas Nüchter, Kai Lingemann, Joachim Hertzberg, and Hartmut Surmann. Heuristic-Based Laser Scan Matching for Outdoor 6D SLAM, in KI 2005: Advances in Artificial Intelligence. 28th Annual German Conference on AI, Proceedings. Springer (Berlin) LNAI vol. 3698, ISBN 3-540-28761-2, pages 304-319. Koblenz, Germany, September 2005. [Get Paper and Video]

Abstract: 6D SLAM (Simultaneous Localization and Mapping) or 6D Concurrent Localization and Mapping of mobile robots considers six dimensions for the robot pose, namely, the x, y and z coordinates and the roll, yaw and pitch angles. Robot motion and localization on natural surfaces, e.g., driving with a mobile robot outdoor, must regard these degrees of freedom. This paper presents a robotic mapping method based on locally consistent 3D laser range scans. Scan matching, combined with a heuristic for closed loop detection and a global relaxation method, results in a highly precise mapping system for outdoor environments. The mobile robot Kurt3D was used to acquire data of the Schloss Birlinghoven campus. The resulting 3D map is compared with ground truth, given by an aerial photograph.

Andreas Nüchter, Kai Lingemann, Joachim Hertzberg, and Hartmut Surmann. Accurate Object Localization in 3D Laser Range Scans, in Proceedings of the 12th International Conference on Advanced Robotics (ICAR '05), ISBN 0-7803-9178-0, pages 665 - 672, Seattle, USA, July 2005, [Get Paper (PDF)] [Get Paper (HTML)].

Abstract: This paper presents a novel method for object detection and classification in 3D laser range data that is acquired by an autonomous mobile robot. Unrestricted objects are learned using classification and regression trees (CARTs) and using an Ada Boost learning procedure. Off-screen rendered depth and reflectance images serve as an input for learning. The performance of the classification is improved by combining both sensor modalities, which are independent from external light. This enables highly accurate, fast and reliable 3D object localization with point matching. Competitive learning is used for evaluating the accuracy of the object localization.

Andreas Nüchter, Kai Lingemann, Joachim Hertzberg, and Hartmut Surmann. 6D SLAM with Approximate Data Association, in Proceedings of the 12th International Conference on Advanced Robotics (ICAR '05), ISBN 0-7803-9178-0, pages 242 - 249, Seattle, USA, July 2005, [Get Paper (PDF)] [Get Paper (HTML)].

Abstract: This paper provides a new solution to the simultaneous localization and mapping (SLAM) problem with six degrees of freedom. A fast variant of the Iterative Closest Points (ICP) algorithm registers 3D scans taken by a mobile robot into a common coordinate system and thus provides relocalization. Hereby, data association is reduced to the problem of searching for closest points. Approximation algorithms for this searching, namely, approximate kd-trees and box decomposition trees, are presented and evaluated in this paper. A solution to 6D SLAM that considers all free parameters in the robot pose is built based on 3D scan matching.

Andreas Nüchter, Oliver Wulf, Kai Lingemann, Joachim Hertzberg, Bernardo Wagner, and Hartmut Surmann, 3D Mapping with Semantic Knowledge, in Proceedings of the RoboCup International Symposium 2005, Osaka, Japan, July 2005, [Get Paper (PDF)] [Get Paper (HTML)].

Abstract: A basic task of rescue robot systems is mapping of the environment. Localizing injured persons, guiding rescue workers and excavation equipment requires a precise 3D map of the environment. This paper presents a new 3D laser range finder and novel scan matching method for the robot Kurt3D [9]. Compared to previous machinery [12], the apex angle is enlarged to 360 . The matching is based on semantic information. Surface attributes are extracted and incorporated in a forest of search trees in order to associate the data, i.e., to establish correspondences. The new approach results in advances in speed and reliability.

Andreas Nüchter, Kai Lingemann, Joachim Hertzberg, Hartmut Surmann, Kai Pervölz, Matthias Hennig, K. R. Tiruchinapalli, Rainer Worst, and Thomas Christaller, Mapping of Rescue Environments with Kurt3D, in Proceedings of the International Workshop on Safty, Security and Rescue Robotics (SSRR '05), ISBN 0-7803-8946-8, pages 158 - 163, Kobe, Japan, June 2005, (best paper award) [Get Paper (PDF)].

Abstract: Deploying rescue workers in an urban setting is often a perilous, time-, power-, and force-consuming job, and systems to assist in this effort are needed. A fundamental task for rescue is to localize injured persons. To this end, robotic systems are used for mapping a site and for remote inspection of suspicious objects. The mobile robot Kurt3D is the first rescue robot that is capable of mapping its environment in 3D and self localize in all six degrees of freedom, i.e., considering its x, y and z positions and the roll, yaw and pitch angles.

Sara Mitri, Simone Frintrop, Kai Pervölz, Hartmut Surmann, and Andreas Nüchter. Robust Object Detection at Regions of Interest with an Application in Ball Recognition, in Proceedings IEEE 2005 International Conference Robotics and Automation (ICRA '05), ISBN 0-7803-8915-8, pages 126 - 131, Barcelona, Spain, April 2005, [Get Paper (PDF)] [Get Paper (HTML)].

Abstract: In this paper, we present a new combination of a biologically inspired attention system (VOCUS Visual Object detection with a Computational attention System) with a robust object detection method. As an application, we built a reliable system for ball recognition in the RoboCup context. Firstly, VOCUS finds regions of interest generating a hypothesis for possible locations of the ball. Secondly, a fast classifier verifies the hypothesis by detecting balls at regions of interest. The combination of both approaches makes the system highly robust and eliminates false detections. Furthermore, the system is quickly adaptable to balls in different scenarios: The complex classifier is universally applicable to balls in every context and the attention system improves the performance by learning scenario-specific features quickly from only a few training examples. Index Terms - visual attention, object classification.

Simone Frintrop, Andreas Nüchter, Hartmut Surmann, and Joachim Hertzberg. Saliency-based Object Recognition in 3D Data, in Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS '04), ISBN 0-7803-8464-4, pages 2167 - 2172, Sendai, Japan, September 2004. [Get Paper (PDF)]

Abstract: This paper presents a robust and real-time capable recognition system for the fast detection and classification of objects in spatial 3D data. Depth and reflection data from a 3D laser scanner are rendered into images and fed into a saliency-based visual attention system that detects regions of potential interest. Only these regions are examinated by a fast classifier. The time saving of classifying objects in salient regions rather than in complete images is linear with the number of trained object classes. Robustness is achieved by the fusion of the bi-modal scanner data; in contrast to camera images, this data is completely illumination independent. The recognition system is trained for two different object classes and evaluated on real indoor data.

Kai Lingemann, Hartmut Surmann, Andreas Nüchter, and Joachim Hertzberg. Indoor and Outdoor Localization for Fast Mobile Robots, in Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS '04), ISBN 0-7803-8464-4, pages 2185 - 2190, Sendai, Japan, September 2004. [Get Paper (PDF)]

Abstract: This paper describes a novel, laser-based approach for tracking the pose of a high-speed mobile robot. The algorithm is outstanding in terms of accuracy and computational time, being 33 times faster than real time. The efficiency is achieved by a closed form solution for the matching of two laser scans, the use of natural landmarks and fast linear filters. The implemented algorithm is evaluated with the high-speed robot Kurt3D (4 m/s), and compared to standard scan matching methods in indoor and outdoor environments.

Sara Mitri, Kai Pervölz, Hartmut Surmann, and Andreas Nüchter. Fast Color-Independent Ball Detection for Mobile Robots, in Proceedings of the IEEE International Conference Mechatronics and Robotics 2004 (MechRob '04), ISBN 3-938153-50-X, pages 900 - 905, Aachen, Germany, September 2004. [Get Paper (PDF)] [Get Paper (HTML)]

Abstract: This paper presents a novel scheme for fast color invariant ball detection in the RoboCup context. Edge filtered camera images serve as an input for an Ada Boost learning procedure that constructs a cascade of classification and regression trees (CARTs). Our system is capable to detect different soccer balls in the RoboCup and other environments. The resulting approach for object classification is real-time capable and reliable.

Sandor Fekete, Rolf Klein, and Andreas Nüchter. Online Searching with an Autononmous Robot, in Algorithmic Foundations of Robotics VI, STAR 17 (Proccedings of the 6th International Workshop on the Algorithmic Foundations of Robotics (WAFR '04)), Springer Tracts in Advanced Robotics, Vol. 17, ISBN 3-540-25728-4, pages 139 - 154, Zeist/Utrecht, The Netherlands, July 2004 (2005), [Get Paper and Video]

Abstract: We discuss online strategies for visibility-based searching for an ob ject hidden behind a corner, using Kurt3D, a real autonomous mobile robot. This task is closely related to a number of well-studied problems. Our robot uses a threedimensional laser scanner in a stop, scan, plan, go fashion for building a virtual three-dimensional environment. Besides planning tra jectories and avoiding obstacles, Kurt3D is capable of identifying objects like a chair. We derive a practically useful and asymptotically optimal strategy that guarantees a competitive ratio of 2, which differs remarkably from the well-studied scenario without the need of stopping for surveying the environment. Our strategy is used by Kurt3D, documented in a separate video.

Andreas Nüchter, Hartmut Surmann, Kai Lingemann, and Joachim Hertzberg. 6D SLAM - Preliminary Report on closing the loop in Six Dimensions, in Proceedings of the 5th IFAC Symposium on Intelligent Autonomous Vehicles (IAV '04), Elsevier, ISBN 008-044237-4, Lissabon, Portugal, June 2004 (2005), [Get Paper and Video].

Abstract: To create 3D volumetric maps of scenes with autonomous mobile robots it is necessary to gage several 3D scans and to merge them into one consistent 3D model. This paper provides a new solution to the simultaneous localization and mapping (SLAM) problem with six degrees of freedom. Robot motion on natural surfaces has to cope with yaw, pitch and roll angles, turning pose estimation into a problem in six mathematical dimensions. A fast variant of the Iterative Closest Points (ICP) algorithm registers the 3D scans in a common coordinate system and relocalizes the robot. Finally, consistent 3D maps are generated using closing loop detection and a global relaxation. Keywords: autonomous mobile robots, 3D laser scanner, 3D scan matching, simultaneous localization and mapping (SLAM), closing loop.

Sandor Fekete, Rolf Klein, and Andreas Nüchter. Searching with an Autononmous Robot, in Proccedings of the 20th ACM Annual Symposium on Computational Geometry (SoCG '04), pages 449 - 450, ACM Press, ISBN 1-58113-885-7, New York, USA, June 2004, [Get Abstract and Video].

Abstract: We demonstrate how one of the classical areas of computational geometry has reached practical application, which in turn gives rise to new, fascinating geometric problems. In particular, we discuss the problem of developing a good online strategy for an autonomous mobile robot to locate an object that is hidden behind a corner or door.

Kai Pervölz, Andreas Nüchter, Hartmut Surmann, and Joachim Hertzberg. Automatic Reconstruction of Colored 3D Models in Proceedings of Robotik 2004, VDI-Berichte 1841, pages 215 - 222, Munich, Germany, ISBN 3-18-091841-1, June 2004, [Get Paper (PDF)] [HTML version].

Abstract: A basic issue of mobile robotics is the automatic generation of environment maps. This paper presents novel results for the reconstruction of textured 3D maps with an autonomous mobile robot, a 3D laser range finder and two pan-tilt color cameras. Building 3D maps involves a number of fundamental scientific issues. This paper adresses the issue of how to fuse the geometry data of the 3D laser range finder with camera images. The proposed algorithm allows to texturize geometrical 3D scenes-models.

Simone Frintrop, Andreas Nüchter and Hartmut Surmann. Visual Attention for Object Recognition in Spatial 3D Data, in: Proceedings of 2nd International Workshop on Attention and Performance in Computational Vision (WAPCV '04), Paletta, L., Tsotsos, J.K., Rome, E., and Humphreys, G. (Eds), ISBN 3-540-24421-2, Revised Selected Papers Series: Lecture Notes in Computer Science, Vol. 3368. Conference: Prague, Czech Republic, May 15, 2004, [Get Paper (PDF)].

Abstract: In this paper, we present a new recognition system for the fast detection and classification of objects in spatial 3D data. The system consists of two main components: A biologically motivated attention system and a fast classifier. Input is provided by a 3D laser scanner, mounted on an autonomous mobile robot, that acquires illumination independent range and reflectance data. These are rendered into images and fed into the attention system that detects regions of potential interest. The classifier is applied only to a region of interest, yielding a significantly faster classification that requires only 30% of the time of an exhaustive search. Furthermore, both the attention and the classification system benefit from the fusion of the bi-modal data, considering more object properties for the detection of regions of interest and a lower false detection rate in classification.

Andreas Nüchter, Hartmut Surmann, Kai Lingemann, Joachim Hertzberg, and Sebastian Thrun. 6D SLAM with Application in Autonomous Mine Mapping, in Proceedings IEEE 2004 International Conference Robotics and Automation (ICRA '04), New Orleans, USA, Omnipress, ISBN 0-7803-8233-1, pages 1998 - 2003, April 2004, [Get Paper (PDF)] [HTML version] [Get Video].

Abstract: To create with an autonomous mobile robot a 3D volumetric map of a scene it is necessary to gage several 3D scans and to merge them into one consistent 3D model. This paper provides a new solution to the simultaneous localization and mapping (SLAM) problem with six degrees of freedom. Robot motion on natural surfaces has to cope with yaw, pitch and roll angles, turning pose estimation into a problem in six mathematical dimensions. A fast variant of the Iterative Closest Points algorithm registers the 3D scans in a common coordinate system and relocalizes the robot. Finally, consistent 3D maps are generated using a global relaxation. The algorithms have been tested with 3D scans taken in the Mathies mine, Pittsburgh, PA. Abandoned mines pose significant problems to society, yet a large fraction of them lack accurate 3D maps.

Dominik Giel, Susanne Frey, Andrea Thelen, Jens Bongartz, Peter Hering, Andreas Nüchter, Hartmut Surmann, Kai Lingemann, and Joachim Hertzberg. Ultra-fast holographic recording and automatic 3D scan matching of living human faces, in PERSPECTIVE IN IMAGE-GUIDED SURGERY, Proceedings of the Scientific Workshop Medical Robotics, Navigation and Visualization (MRNV '04), World Scientific, ISBN 981-238-872-9, Book of Abstracts: ISBN 3-9807690-5-4 (Kreative Konzepte, Remagen), Remagen, Germany, March 2004 [Get Paper (PDF)] [HTML version]

Abstract: 3D models of the skin surface of patients are created by ultra-fast holography and automatic scan matching of synchronously recorded holograms. By recording with a pulsed laser and continuous-wave optical reconstruction of the holographic real image, motion artifacts are eliminated. Focal analys is of the real image yields a surface relief of the patient. To generate a complete 360 patient model, several synchronously recorded reliefs are registered by automatic scan matching. We find the transformation consisting of a rotation and a translation that minimizes a cost function containing the Euclidian distances between points pairs from two surface relief maps. A variant of the ICP (Iterative Closest Points) algorithm2 is used to compute such a minimum. We propose a new fast approximation based on kDtrees for the problem of creating the closest point pairs on which the ICP algorithm spends most of its time.

Andreas Nüchter, Hartmut Surmann, and Joachim Hertzberg. Automatic Classification of Objects in 3D Laser Range Scans, in Proceedings of the 8th Conference on Intelligent Autonomous Systems (IAS '04), IOS Press, ISBN 1-58603-414-6, pages 963 - 970, Amsterdam, The Netherlands, March 2004, [Get Paper (PDF)] [HTML version].

Abstract: This paper presents a new method for object detection and classification in 3D laser range data that is acquired by an autonomous mobile robot. Off-screen rendered depth and reflectance images serve as an input for an Ada Boost learning procedure that constructs a cascade of classifiers. The performance of the classification is improved by combining both sensor modalities, which are independent from external light. The resulting approach for object classification is real-time capable and reliable. It combines recent results in computer vision with the emerging technology of 3D laser scanners.

Andreas Nüchter. Schnelle Visualisierung von Radialen 3D-Laserscans in Proceedings of the 5. Fachwissenschaftlicher Informatikkongress - Informatiktage 2003, ISBN 3-920560-21-3, pages 243 - 246, Bad Schussenried, Germany, November 2003 (2004).

Andreas Nüchter, Hartmut Surmann, Kai Lingemann, Kai Pervölz, and Joachim Hertzberg. Video: Autonomous Mobile Robots for 3D Digitalization of Environments, in Video Theatre of the 4th IEEE International Conference on Recent Advances in 3D Digital Imaging and Modeling (3DIM '03), Banff, Canada, October 2003, [Download Video].

Johannes Schauer and Andreas Nü Joachim Hertzberg. Automatic Model Refinement for 3D Reconstruction with Mobile Robots, in Proceedings of the 4th IEEE International Conference on Recent Advances in 3D Digital Imaging and Modeling (3DIM '03), IEEE Computer Society Press, ISBN 0-7695-1991-1, pages 394 - 401, Banff, Canada, October 2003, [Get Paper (PDF)] [HTML Version].

Abstract: Precise digital 3D models of indoor environments are needed in several applications, e.g., facility management, architecture, rescue and inspection robotics. This paper presents a new algorithm that transforms a 3D volumetric model into a very precise compact 3D map and generates semantic descri ptions. Our system is composed of a robust, autonomous mobile robot for the automatic data acquisition and a precise, cost effective, high quality 3 D laser scanner to gage indoor environments. The reconstruction method consists of reliable scan matching and feature detection algorithms. The 3D scene is matched against a coarse semantic description of general indoor environments and the generated knowledge is used to refine the 3D model.

Andreas Nüchter, Hartmut Surmann, Kai Lingemann, Joachim Hertzberg: Consistent 3D Model Construction with Autonomous Mobile Robots in: A. Günter et al. (eds.): KI 2003: Advances in Artificial Intelligence. 26th Annual German Conference on AI, Proceedings Springer LNAI vol. 2821, ISBN 3-540-20059-2, pages 550 - 564, Hamburg, Germany, September 2003, [Get Paper (PDF)] [HTML Version].

Abstract: Digital 3D models of the environment are needed in facility management, architecture, rescue and inspection robotics. To create 3D volumet ric models of scenes, rooms or buildings, it is necessary to gage several 3D scans and to merge them into one consistent 3D model. This paper presen ts a system, composed of a fast and robust, autonomous mobile robot, a precise, cost effective, high quality 3D laser scanner, and reliable scan mat ching algorithms for measuring and reconstructing environments, capable of matching two 3D scans within a fraction of a second. The proposed new sof tware modules for scan matching are fast variants of the iterative closest point algorithm (ICP) for consistent alignment. Two applications are presented: First, the reconstruction of an office environment, second, the fitting of sewer pipes into 3D data to detect deviations from the spatial geometry.

Andreas Nüchter, Hartmut Surmann, and Joachim Hertzberg. Planning Robot Motion for 3D Digitalization of Indoor Environments, in Proceedings of the 11th International Conference on Advanced Robotics (ICAR '03), pages 222 - 227, ISBN 972-96889-9-0, Coimbra, Portugal, June 2003, [Get Paper (PDF)] [HTML Version].

Abstract: 3D digitalization of environments without occlusions requires multiple 3D scans. Autonomous mobile robots equipped with a 3D laser scanner are wel l suited for the gaging task. They need an efficient exploration scheme for the digitalization. We present a new approach for planning the next scan pose as well as the robot motion. Our approach calculates a collision free trajectory regarding complicated objects, e.g., with jutting out edges. A closed loop and global ly stable motor control ler navigates the mobile robot. The results of a 3D digitalization experiment in the main hall of castle Birlinghoven is presented.

Simone Frintrop, Erich Rome, Andreas Nüchter, and Hartmut Surmann. An Attentive, Multi-modal Laser Eye, in Proceedings of the third International Conference on Computer Vision Systems (ICVS '03)., J. Crowley, J.H. Piater, M. Vincze, and L. Paletta (eds), pages 202 - 211, Springer LNCS 2626, ISBN 3-540-00921-3, Graz, Austria, April 2003, [Get Paper (PDF)] (copyright Springer Verlag).

Abstract: In this paper we present experimental results on a novel application of visual attention mechanisms for the selection of points of interes t in an arbitrary scene. The imaging sensor used is a multi-modal 3D laser scanner. In a single 3D scan pass, it is capable of providing range data as well as a gray-scale intensity image. The scanner is mounted on top of an autonomous mobile robot and serves control purposes. We present results achieved by applying the visual attention system of Itti et al. [8] to recorded scans of indoor and outdoor scenes. The vast ma jority of the prima ry attended locations pointed to scene ob jects of potential interest for navigation and ob ject detection tasks. Moreover, both sensor modalities c omplement each other, resulting in a greater variety of points of interest than one modality alone can provide.

Simone Frintrop, Erich Rome, Andreas Nüchter, and Hartmut Surmann. Applying Attentional Mechanisms to Bi-modal 3D Laser Data, in International Workshop on Attention and Performance in Computer Vision (WAPCV '03) L. Paletta, G.W. Humphreys, and R.B. Fisher (eds), pages. 25-30, Joanneum Research, Graz, Austria, 2003, [Get Paper (PDF)].

Abstract: In this paper we present experimental results on a novel application of visual attention mechanisms for the selection of points of interest in an ar bitrary scene. The imaging sensor used is a multi-modal 3D laser scanner. In a single 3D scan pass, it is capable of providing range data as well as a gray-scale intensity image. The scanner is mounted on top of an autonomous mobile robot and serves control purposes. We present results achieved by applying the visual attention system of Itti et al. [8] to recorded scans of indoor and outdoor scenes. The vast majority of the primary attended l ocations pointed to scene objects of potential i nterest for navigation and object detection tasks. Moreover, both sensor modalities complement each other, resulting in a greater variety of points of interest than one modality alone can provide.

Andreas Nüchter. Autonome Exploration und 3D-Modellierung der Umgebung eines Roboters in Proceedings of the 4. Fachwissenschaftlicher Informatikkongress - Informatiktage 2002, pages 64 - 68, ISBN 3-920560-17-5, Bad Schussenried, Germany, November 2002 (2003), (best paper award) [Get Paper (PDF)].

Zusammenfassung: Autonome mobile Roboter müssen in der Lage sein, sicher durch ihre Umgebung zu navigieren, um anwendungsspezifische Aufgaben ausführen zu können. Gelingen kann dies nur durch den Einsatz von 3D-Sensoren und 3D-Karten. Daher ist die automatische und schnelle 3D-Modellierung der Umgebung eine wichtige Fragestellung in der Robotik. 3D-Laserscanner sind eine junge Technologie, die die Erfassung räumlicher Daten revolutioniert und Robotern das dreidimensionale Abtasten von Objekten mölich macht. Die vorliegende Arbeit untersucht und evaluiert die zur autonome n 3D-Kartenerstellung notwendigen Algorithmen mit Hilfe des AIS 3D-Laserscanners, der sich auf einer geeigneten Roboterplattform befindet. Das entwickelte System ermöglicht das berhrungslose Abtasten der gesamten Umgebung. Dafür werden mehrere 3D-Scans zu einer konsistenten Szene zusammengefügt sowie Scanpositionen generiert.

Hartmut Surmann, Kai Lingemann, Andreas Nüchter, and Joachim Hertzberg. Fast acquiring and analysis of three dimensional laser range data, in Proceedings of the 6th International Fall Workshop Vision, Modelling, and Visualization 2001 (VMV '01), pages 59 - 66, ISBN 3-89838-028-9, Stuttgart, Germany, November 2001, [Get Paper (PDF)] [HTML Version].

Abstract: This paper presents a precise (1cm), lightweight (5kg) and low cost 3D laser range finder for the fast gaging (1.4 sec) of environments. Real-time algorithms for the data reduction, 3D-object segmentation are also presented. A special designed suspension unit, a standard servo motor and a stan dard 2D range finder are used to build the 3D scanner. Maximal resolutions e.g. 180 (h) 90 (v) degree with 194400 points are grabbed in 8.1 seconds and low resolutions with 16200 points are grabbed in 1.4 seconds. While scanning, different online algorithms for line and surface detection are applied to the data. 3D-Object segmentation and detection are done offline after the scan. With the proposed approach, a precise, reliable, mobile, low cost, and real-time capable 3D sensor for the contact-less measuring of environments without additional landmarks is available.

Andreas Nüchter, Kai Lingemann. Ein 3D Laserscanner für autonome mobile Roboter, in Proceedings of the 3. Fachwissenschaftlicher Informatikkongress - Informatiktage 2001, pages 89 - 92, Bad Schussenried, Germany, November 2001 (2002), [Get Paper (PDF)].

Hartmut Surmann, Kai Lingemann, Andreas Nüchter, and Joachim Hertzberg. A 3D laser range finder for autonomous mobile robots, in Proceedings of the 32nd International Symposium on Robotics (ISR '01), pages 153 - 158, ISBN 89-88366-04-2, Seoul, Korea, May 2001, [Get Paper (PDF)].

Abstract: This paper presents a high quality, low cost 3D laser range finder designed for autonomous mobile systems. The 3D laser is built on the bas e of a 2D range finder by the extension with a standard servo. The servo is controlled by a computer running RT-Linux. The scan resolution (5 cm) f or a complete 3D scan of an area of 150 (h) 90 (v) degree is up to 115000 points and can be grabbed in 12 seconds. Standard resolutions e.g. 150 (h) 90 (v) degree with 22500 points are grabbed in 4 seconds. While scanning, different online algorithms for line and surface detection are applied to the data. Object segmentation and detection are done offline after the scan. The implemented software modules detect overhanging objects blocking t he path of the robot. With the proposed approach a cheap, precise, reliable and real-time capable 3D sensor for autonomous mobile robots is availabl e and the robot navigation and recognition in real-time is improved. 1. Introduction Prognoses at the beginning of the nineties claimed for the new millennium a number of about 50.000 independently operating autonomous service robots in different areas of production and service sectors [1]. The reality is different. In industrial environments guided vehicles, i.e. vehicles guided by a magnetic or optical track are standard [2]. Autonomous mobile service systems, i.e. systems not restricted by a track, are used extremely rarely although many research groups are working on this since sev eral years particularly with mobile systems for transportation tasks, e.g. [3, 4, 5, 6]. One of several reasons for the gap between prognoses and r eality is the lack of good, cheap and fast sensors that allow the robots to sense the environment in real-time and to act on the basis of the acquir ed data. This paper presents a 3D laser range finder designed for autonomous mobile systems (fig. 1). A large number of today's autonomous robots us e 2D laser range finders as a proximity sensor. They are very fast (processing time 30 ms), precise ( 1 cm, ) and becoming cheaper ($3000) since th ere are at least two competing products [7, 8].

Ming Li, Wei Li, Jian Wang, Qingquan Li, and Andreas Nüchter Towards Reliable Object Anchoring in Highly Dynamic Traffic Scenes in ICRA 2012 WORKSHOP Semantic Perception and Mapping for Knowledge-enabled Service Robotics (with interactive session and demonstrations), St. Paul, MN, USA, May 2012.

Dorit Borrmann, Jan Elseberg, and Andreas Nüchter. Thermal 3D Mapping for Saving Energy. Proceedings of the 5th International Conference on Cognitive Systems (COGSYS '12), [Get Poster (PDF)].

Martin Magnusson, Andreas Nüchter, Christopher Lörken, Achim J. Lilienthal, and Joachim Hertzberg. 3D Mapping the Kvarntorp Mine: A Field Experiment for Evaluation of 3D Scan Matching Algorithms. In Proceedings of the Workshop on 3D-Mapping at the IEEE International Conference on Intelligent Robots and Systems (IROS '08), Nice, France, September 2008.

Thomas Wiemann, Andreas Nüchter, Kai Lingemann, Stefan Stiene, and Joachim Hertzberg. Surface Reconstruction for 3D Robotic Mapping. In Proceedings of the Workshop on 3D-Mapping at the IEEE International Conference on Intelligent Robots and Systems (IROS '08), Nice, France, September 2008.

Stefan Stiene, Andreas Nüchter, Kai Lingemann, and Joachim Hertzberg. An Experiment in Semantic Correction of Sensor Data, (Poster) in Proceedings Workshop on Semantic Information in Robotics at the IEEE International Conference Robotics and Automation (ICRA '07), Rome, Italy, April 2007, [Get Paper (PDF)].

Johannes Steger, Robert Märtin, Kai Lingemann, Andreas Nüchter, Joachim Hertzberg, and Peter König. Laser range scans of natural scenes for the evaluation of stereo- matching algorithms. Poster at ICVS Workshop From Computational Cognitive Neuroscience to Computer Vision (CCNCV '07) Bielefeld, Germany, March 2007.

Johannes Steger, Robert Märtin, Kai Lingemann, Andreas Nüchter, Joachim Hertzberg, and Peter König. Assessing stereo matching algorithms using ground-truth disparity maps of natural scenes, (Poster), in Proceedings of the 7th Meeting of the German Neuroscience Society / 31th Göttingen Neurobiology Conference, Neuroforum 2007, Göttingen, Germany, 2007.

Simone Frintrop, Erich Rome, Andreas Nüchter, and Hartmut Surmann, Focussing Object Recognition on Regions of Interest, in Proceedings of the 7. Tübingen Perception Conference (TWK '04), H. Bülthoff, H.A. Mallot, R. Ulrich, F.A. Wichmann (eds), page 67, Tübingen, Germany, February, 2004.

Simone Frintrop, Erich Rome, Andreas Nüchter, and Hartmut Surmann, Visuelle Aufmerksamkeitsmechanismen auf bimodalen Laserdaten, in Beiträge zur 6. Tübinger Wahrnehmungskonferenz (TWK '03), H. Bülthoff, K.R. Gegenfurtner, H.A. Mallot, R. Ulrich, F.A. Wichmann (eds), page 100, Tübingen, Germany, February, 2003.

Kai Lingemann, Andreas Nüchter, Joachim Hertzberg, Oliver Wulf, Bernardo Wagner, Kai Pervölz, Hartmut Surmann, and Thomas Christaller. RoboCupRescue2006 – Robot League, Deutschland1 (Germany), in Team Description Paper, Rescue Robot League Competition, (CDROM Proceedings), Bremen, Germany, June 2006, [Get Paper (PDF)].

Abstract: After scoring second in RoboCup Rescue 2004 with Kurt3D and participating in 2005 with two robots, namely Kurt3D and RTS Crawler, we concentrated on the development of interaction between both vehicles. Kurt3D is able to autonomously explore and map the environment in 3D and search for victims. The RTS Crawler is designed to access more demanding territory (i.e., red arena), working either remote controlled or semi-autonomous. The key innovation of this system lies in the capability for autonomous 6D SLAM (simultaneous localization and mapping) and 3D map generation of natural scenes, combined with the intelligent cooperation between robots that enables one operator to efficiently map and explore the whole arena.
The robots are equipped with dedicated state of the art equipment, e.g., 3D laser range finders, infrared camera and CO2-sensor. Robots as well as operator station are rather compact and easy to set up. The challenge of controlling two rescue robots with only one operator is managed with a redesigned user interface and a number of autonomous and semi-autonomous features.

Andreas Nüchter, Kai Lingemann, and Joachim Hertzberg. Kurt3D – A Mobile Robot for 3D Mapping of Environments, ELROB Technical Paper, Hammelburg, Germany, May 2006. [Get Technical Paper (PDF)] [Get Team Information (PDF)] [Get Vehicle Specification Sheet (PDF)] [Get Team Roster (PDF)].

Abstract: The mobile robot Kurt3D is the first robot that is capable of mapping its environment in 3D and self localize in all six degrees of freedom, i.e., considering its x, y and z positions and the roll, yaw and pitch angles. Robot motion on natural surfaces has to cope with yaw, pitch and roll angles, turning pose estimation into a problem in six mathematical dimensions. Kurt3D creates a consistent volumetric scene in a common coordinate frame from multiple 3D laser scans. To create 3D volumetric maps it is necessary to gage several 3D scans and register them into one consistent 3D model. A fast variant of the Iterative Closest Points (ICP) algorithm is used for registration and relocalization.

Hartmut Surmann, Kai Lingemann, Andreas Nüchter, Matthias Hennig, Kai Pervölz, Oliver Wulf, Joachim Hertzberg, Bernardo Wagner, and Thomas Christaller. RoboCupRescue - Robot League Team, Team Deutschland1 (Germany) Team Description Paper, Rescue Robot League Competition, (RoboCup 2005), (CDRom Proceedings), Osaka, Japan, July 2005, (6th place), [Get Paper (PDF)].

Abstract: After the second place in RoboCup Rescue 2004, a new version of the mobile robot Kurt3D was developed in our groups during the last year [1]. The key innovation of this system lies in the capability for autonomous or operator-assisted 6D SLAM (simultaneous localization and mapping) and 3D map generation of natural scenes. Hence, Kurt3D already meets the basic requirement regarding urban search and rescue. For the rescue robot league competition, it is additionally configured with dedicated state-of-the-art equipment e.g. infrared camera and CO2sensor. The robot and the operator station are rather compact and easy to set up. The operator uses a joystick as a remote control for the robot and can watch a live video of the scene where the robot drives. Data are transmitted via wireless LAN. A 3D laser scanner, which is mounted on an outdoor variant of Kurt3D, is used as the main sensor for map generation as well as for navigation and localization. The whole system has been used with a proven record of success for different tasks of map building, so that we are confident of managing the rescue robot league competition, too.

Hartmut Surmann, Rainer Worst, Matthias Hennig, Kai Lingemann, Andreas Nüchter, Kai Pervoelz, Kiran Raj Tiruchinapalli, Thomas Christaller, and Joachim Hertzberg. RoboCup Rescue - Robot League Team KURT3D, Germany, Team Description Paper, Rescue Robot League Competition (CDROM Proceedings RoboCup 2004), Portugal, July 2004, (vice world champion), [Get Paper].

Abstract: A mobile robot named KURT3D was developed at the Fraunhofer Institute for Autonomous Intelligent Systems during the last three years. The key innovation of this system lies in the capability for autonomous or operatorassisted 6D SLAM (simultaneous localization and mapping) and 3D map generation of natural scenes. Hence, KURT3D already meets the basic requirement regarding urban search and rescue. For the rescue robot league competition, it is additionally configured with dedicated state-of-the-art equipment. The robot and the operator station are rather compact and easy to set up. The operator uses a joystick as a remote control for the robot and can watch a live video of the scene where the robot drives. Data are transmitted via wireless LAN. A 3D laser scanner, which is mounted on an outdoor variant of KURT3D, is used as the main sensor for map generation as well as for navigation and localization. The whole system has been used with a proven record of success for different tasks of map building, so that we a reconfident of managing the rescue robot league competition, too.

Hartmut Surmann, Andreas Nüchter, and Joachim Hertzberg. Autonomous Mobile Robots for 3D Digitalization of Indoor Environments, GMD Report 147, ISSN 1435-2702, Sankt-Augustin, Germany, 2003.

Andreas Nüchter. Autonome Exploration und Modellierung von 3D-Umgebungen Diplomarbeit an der Universität Bonn, Bonn, Germany Juli 2002, also appeared as GMD-Report 157, ISBN 3-88457-979-7, Sankt Augustin, Germany, July 2002, [Get Paper (PDF)] [HTML Version].

Zusammenfassung: Autonome mobile Roboter müssen in der Lage sein, sicher durch ihre Umgebung zu navigieren, um anwendungsspezifische Aufgaben ausführen zu können. Gelingen kann dies nur durch den Einsatz von 3D-Sensoren und 3D-Karten. Daher ist die automatische und schnelle Modellierung der Umgebung eine wichtige Fragestellung in der Robotik. 3D-Laserscanner sind eine junge Technologie, die die Erfassung räumlicher Daten revolutioniert und Robotern das dreidimensionale Abtasten von Objekten möglich macht. Die vorliegende Arbeit untersucht und evaluiert die zur autonomen 3D-Kartenerstellung notwendigen Algorithmen mit Hilfe des AIS 3D-Laserscanners, der sich auf einer geeigneten Roboterplattform befindet. Das entwickelte System ermöglicht dabei das berührungslose Abtasten der gesamten Umgebung. Der erste Teil der Arbeit beschäftigt sich mit der Aufgabe, 3D-Scans in einem globalen Koordinatensystem zu registrieren. Die von der Odometrie des Roboters geschätzte Pose (Position a und Orientierung) wird dabei korrigiert. Verschiedene Variationen des iterativen Algorithmus der nächsten Punkte (ICP) kommen zum Einsatz. Im zweiten Teil geht es darum, eine möglichst optimale nächste Scanposition zu bestimmen, von der aus unbekanntes Terrain erforscht werden kann. Ein randomisierter Approximationsalgorithmus plant die neue Posi tion des Scanners. Anschliessend ist diese Position durch eine geeignete Motorregelung anzufahren, wobei Kollisionsvermeidung berucksichtigt wird. Schliesslich werden die Ergebnisse in geeigneter Weise, unter anderem durch Gittermodelle, visualisiert. Schlagwörter: 3D-Laserscanner, 3D-Modellierung, 3D-Kartenerstellung, Scanmatching, iterativer Algorithmus der nchsten Punkte, autonome Exploration, simultanes Lokalisationsa und Kartierungsproblem, Approximation der nächsten optimalen Scanposition, Robotersteuerung, Oberflächenreprsentation durch Gittermodelle.

Hartmut Surmann, Kai Lingemann, Andreas Nüchter, and Joachim Hertzberg. Aufbau eines 3D-Laserscanners für autonome mobile Roboter, GMD-Report 126, ISBN 3-88457-974-6, Sankt Augustin, Germany, March 2001, [Abstract] [Get Paper (PDF)] [HTML Version].

Zusammenfassung: Diese Ausarbeitung stellt das Konzept und die Realisierung eines 3D-Laserscanners vor. Ziel der Realisierung war es, das Dreieck aus Kosten, Geschwindigkeit und Qualität so zu optimieren, dass der 3D-Scanner auf autonomen mobilen Robotern sinnvoll zur Exploration und Navigation eingesetzt werden kann. Ein auf autonomen mobile Fahrzeugen häufig verwendeter 2D-Laserscanner wurde dazu mittels einer selbst konstruierten Aufhängung und eines Servomotors aufgerüstet. Mittels des auf einem Standardrechner laufenden Echtzeitbetriebssystem RT-Linux steuert der Servomotor den 3D Laserscanner direkt an. Unterschiedliche Online-Algorithmen zur Linienerkennung und Flächendetektion bilden die Software-Basis des 3D Scanners. Offline-Algorithmen zur Objektsegmentierung und Erkennung sowie ein 3D-Visualisierungsprogramm runden das Softwarepaket ab.

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Bertram Koch, Robin Leblebici, Angel Martell, Sven Jörissen, Klaus Schilling, and Andreas Nüchter. Evaluating continuous-time SLAM using a predefined trajectory provided by a robotic arm. in Proceedings of the ISPRS Geospatial Week 2017, Laserscanning 2017, ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., Wuhan, China 2017, [Get Paper].

Abstract: Recently published approaches to SLAM algorithms process laser sensor measurements and output a map as a point cloud of the environment. Often the actual precision of the map remains unclear, since SLAM algorithms apply local improvements to the resulting map. Unfortunately, it is not trivial to compare the performance of SLAM algorithms objectively, especially without an accurate ground truth. This paper presents a novel benchmarking technique that allows to compare a precise map generated with an accurate ground truth trajectory to a map with a manipulated trajectory which was distorted by different forms of noise. The accurate ground truth is acquired by mounting a laser scanner on an industrial robotic arm. The robotic arm is moved on a predefined path while the position and orientation of the end-effector tool are monitored. During this process the 2D profile measurements of the laser scanner are recorded in six degrees of freedom and afterwards used to generate a precise point cloud of the test environment. For benchmarking, an offline continuous-time SLAM algorithm is subsequently applied to remove the inserted distortions. Finally, it is shown that the manipulated point cloud is reversible to its previous state and is slightly improved compared to the original version, since small errors that came into account by imprecise assumptions, sensor noise and calibration errors are removed as well.

Johannes Schauer and Andreas Nüchter. Digitizing automotive production lines without interrupting assembly operations through an automatic voxel-based removal of moving objects. in Proceedings of the 13th IEEE International Conference on Control and Automation (ICCA '17), Ohrid, Macedonia, July 2017. [Get Paper].
Also presented at the IEEE ICRA workshop on IC3 - Industry of the Future: Collaborative, Connected, Cognitive. Novel Approaches Stemming from Factory of the Future & Industry 4.0 Initiatives

Abstract: We present an efficient method to partition a point cloud gathered through kinematic laser scanning into static and dynamic points. The presented algorithm utilizes a voxel grid data structure and uses a ray intersection test to mark voxels as dynamic. The algorithm does not require any ego-motion estimations, computationally expensive object recognition or tracking of moving objects over time. It is easy to implement and can be executed on many cores in parallel. We show the viability of this approach by applying our algorithm to a dataset that we gathered by mounting a FARO Focus3D Laser scanner onto a skid which was then sent along a production line for consumer car chassis in a factory of the Volkswagen corporation. Since factory operators are interested in acquiring digital models of their production lines without suspending factory operations, the resulting point cloud will contain many dynamic objects like humans or other car bodies. We show how our algorithm is able to successfully remove these dynamic objects from the resulting point cloud with minimal errors. Our implementation is published under a free license as part of 3DTK.

Michael Bleier, André Dias, António Ferreira, John Pidgeon, José Miguel Almeida, Eduardo Silva, Klaus Schilling, and Andreas Nüchter. Signed Distance Function Based Surface Reconstruction of a Submerged Inland Mine Using Continuous-time SLAM. in Proceedings of the 20th World Congress of the International Federation of Automatic Control (WC '17), Toulouse, France, July 2017. [Get Paper].

Abstract: The planning of mining operations in water filled open-pit mines requires detailed bathymetry to create a mine plan and assess the involved risks. This paper presents post- processing techniques for creating an improved 3D model from a survey carried out using an autonomous surface vehicle with a multibeam sonar and a GPS/INS navigation system. Inconsistencies of the created point cloud as a result of calibration errors or GPS signal loss are corrected using a continuous-time simultaneous localization and mapping (SLAM) solution. Signed distance function based mapping is employed to fuse the measurements from multiple runs into a consistent representation and reduce sensor noise. From the signed distance function model we reconstruct a 3D surface mesh. We use this terrain model to establish a virtual reality scene for immersive data visualization of the mining operations for testing and planing during development. Results of the proposed approach are demonstrated on a dataset captured in an abandoned submerged inland mine.

Christian Pfitzner, Stefan May, and Andreas Nüchter. Evaluation of Features from RGB-D Data for Human Body Weight Estimation. in Proceedings of the 20th World Congress of the International Federation of Automatic Control (WC '17), Toulouse, France, July 2017. [Get Paper].

Abstract: Body weight is a crucial parameter when it comes to drug or radiation dosing. In case of emergency treatment time is short so that physicians estimate the body weight by the visual appearance of a patient. Further, visual body weight estimation might be a feature for person identification. This paper presents the anthropometric feature extraction from RGB-D sensor data, recorded from frontal view. The features are forwarded to an artificial neural network for weight estimation. Experiments with 233 people demonstrate the capability of different features for body weight estimation. To prove robustness against sensor modalities, a structured light sensor is used, as well as a time-of-flight sensor. An additional experiment including temperature features from a thermal camera improves the body weight estimation beyond.

Rainer Koch, Stefan May, and Andreas Nüchter. Effective Distinction Of Transparent And Specular Reflective Objects In Point Clouds Of A Multi-Echo Laser Scanner. in Proceedings of the 18th IEEE International Conference on Advanced Robotics (ICAR '17), Hongkong, July 2017. [Get Paper].

Abstract: A favoured sensor for mapping is a 3D laser scanner since it allows a wide scanning range, precise measurements, and is usable indoor and outdoor. Hence, a mapping module delivers detailed and high resolution maps which makes it possible to navigate safely. Difficulties result from transparent and specular reflective objects which cause erroneous and dubious measurements. At such objects, based on the incident angle, measurements result from the object surface, an object behind the transparent surface, or an object mirrored with respect to the reflective surface. This paper describes an enhanced Pre-Filter-Module to distinguish between these cases. Two experiments demonstrate the usability and show that for single scans the identification of mentioned objects in 3D is possible. The first experiment was made in an empty room with a mirror. The second experiment was made in a stairway which contains a glass door. Further, results show that a discrimination between a specular reflective and a transparent object is possible. Especially for transparent objects the detected size is restricted to the incident angle. That is why future work concentrates on implementing a post-filter module. Gained experience shows that collecting the data of multiple scans and postprocess them as soon as the object was bypassed will improve the map.

Rainer Koch, Lena Böttcher, Maximilian Jahrsdörfer, Johannes Maier, Malte Trommer, Stefan May, and Andreas Nüchter. Out of lab calibration of a rotating 2D Scanner for 3D mapping. in Proceedings of the SPIE optical metrology, Videometrics, Range Imaging, and Applications, Munich, Germany, June 2017. [Get Paper].

Abstract: Mapping is an essential task in mobile robotics. To fulfil advanced navigation and manipulation tasks a 3D~representation of the environment is required. Applying stereo cameras or Time-of-flight cameras (TOF cameras) are one way to archive this requirement. Unfortunately, they suffer from drawbacks which makes it difficult to map properly. Therefore, costly 3D laser scanners are applied. An inexpensive way to build a 3D representation is to use a 2D laser scanner and rotate the scan plane around an additional axis.
A 3D point cloud acquired with such a custom device consists of multiple 2D line scans. Therefore the scanner pose of each line scan need to be determined as well as parameters resulting from a calibration to generate a 3D point cloud. Using external sensor systems are a common method to determine these calibration parameters. This is costly and difficult when the robot needs to be calibrated outside the lab. Thus, this work presents a calibration method applied on a rotating 2D laser scanner. It uses a hardware setup to identify the required parameters for calibration. This hardware setup is light, small, and easy to transport. Hence, an out of lab calibration is possible. Additional a theoretical model was created to test the algorithm and analyse impact of the scanner accuracy.
The hardware components of the 3D scanner system are an HOKUYO UTM-30LX-EW 2D laser scanner, a Dynamixel servo-motor, and a control unit. The calibration system consists of an hemisphere. In the inner of the hemisphere a circular plate is mounted. The algorithm needs to be provided with a dataset of a single rotation from the laser scanner. To achieve a proper calibration result the scanner needs to be located in the middle of the hemisphere. By means of geometric formulas the algorithms determine the individual deviations of the placed laser scanner. In order to minimize errors, the algorithm solves the formulas in an iterative process.
First, the calibration algorithm was tested with an ideal hemisphere model created in Matlab. Second, laser scanner was mounted differently, the scanner position and the rotation axis was modified. In doing so, every deviation, was compared with the algorithm results. Several measurement settings were tested repeatedly with the 3D scanner system and the calibration system. The results show that the length accuracy of the laser scanner is most critical. It influences the required size of the hemisphere and the calibration accuracy.

Joachim Hertzberg, Kai Lingemann, and Andreas Nüchter. Mobile Roboter. Eine Einführung aus Sicht der Informatik. Springer, ISBN 978-3642017254, 2012. [Web page] [Springer page] [Get Book from Amazon]

Kurzbeschreibung: Mobile Roboter bewegen sich autonom im Raum. Die dafür notwendigen Berechnungen des Steuerungsprogramms beruhen wesentlich auf Sensordaten aus der Umgebung. Im Zentrum des Lehrbuchs stehen Algorithmen und Repräsentationen für die Steuerung mobiler Roboter. Aufbauend auf Kapiteln zu Sensorik und Sensordatenverarbeitung werden alle zentralen nicht-mechanischen Aspekte der Fortbewegung behandelt. Das erste Lehrbuch in deutscher Sprache zum Thema eignet sich nicht nur für das Bachelor-Studium, sondern auch zum Selbststudium und als Nachschlagewerk.
Buchrückseite: Wo bin ich? Wo soll ich hin? Wie komme ich dahin? Mobile Roboter in Alltagsumgebungen wie in Büros oder auf Straßen müssen ständig solche Fragen beantworten, sollen sie autonom, also ohne Fernsteuerung operieren. Die Berechnungen im Robotersteuerungsprogramm beruhen wesentlich auf Sensordaten aus der Umgebung, die oft unvollständig oder fehlerhaft sind. Das vorliegende Lehrbuch führt aus der Informatik-Perspektive in die entsprechenden Algorithmen und Repräsentationen ein. Ausgehend von Überblicken zu Sensorik und Sensordatenverarbeitung werden alle zentralen Aspekte der Steuerung autonomer mobiler Roboter behandelt: Bewegungsschätzung, Lokalisierung in Karten, Kartierung, Navigation, Umgebungsdateninterpretation und Software-Architekturen zur Robotersteuerung. Das Buch ist aus Lehrveranstaltungen entstanden und ist nicht nur für die Bachelor-Lehre an allen Hochschularten, sondern auch zum Selbststudium und als Nachschlagewerk geeignet.

Andreas Nüchter, Radu B. Rusu, Dirk Holz, and Daniel Munoz. Editorial: Semantic Perception, Mapping and Exploration. Journal of Robotics and Autonomous Systems (JRAS), Special Issue on Semantic Perception, Mapping and Exploration, Volume 62, Issue 5, May 2014. [Get Paper]

Semantic perception, mapping and exploration (SPME) for intelligent systems, such as robots, has seen a lot of progress recently, with many new and interesting techniques. When these intelligent systems are deployed in real-world environments, a variety of challenges are raised. For example, service robots need to plan in spaces exceeding their local perceptual space in order to cope with a wide variety of tasks, and robots operating in human living environments need to aggregate and model perceived semantic information. A further requirement for long-term autonomous operation is the ability to acquire and update the necessary information over time, which involves actively exploring the environment.

Andreas Nüchter. 3D Robotic Mapping. Springer Tracts in Advanced Robotics (STAR), ISBN 978-3540898832, 210 pages, Springer Verlag, 2009. [Springer Link] [Get Book].

About this book: The monograph written by Andreas Nüchter is focused on acquiring spatial models of physical environments through mobile robots. The robotic mapping problem is commonly referred to as SLAM (simultaneous localization and mapping). 3D maps are necessary to avoid collisions with complex obstacles and to self-localize in six degrees of freedom (x-, y-, z-position, roll, yaw and pitch angle). New solutions to the 6D SLAM problem for 3D laser scans are proposed and a wide variety of applications are presented.
Written for: Researchers, Graduate Students and Professionals in Robotics, Computer Vision and Multimedia

Andreas Nüchter. Semantische dreidimensionale Karten für autonome mobile Roboter, Dissertation (PhD thesis), University of Bonn, September 2006, also appeared as DISKI 303, ISBN 3-89838-303-2, Akademische Verlagsgesellschaft Aka GmbH, Berlin, Germany.

Zusammenfassung: Intelligentes autonomes Roboterhandeln in Alltagsumgebungen erfordert den Einsatz von 3D-Karten, in denen Objekte klassifiziert sind. 3D-Karten sind u.a. zur Steuerung notwendig, damit der Roboter komplexen Hindernissen ausweichen und sich mit 6 Freiheitsgraden (x-, y-, z-Position, Nick-, Gier-, und Rollwinkel) lokalisieren kann. Soll der Roboter mit seiner Umgebung interagieren, wird Interpretation unumgänglich. über erkannte Objekte kann der Roboter Schlussfolgerungen ziehen, sein Wissen wird inspizier- und kommunizierbar. Aus diesen Gründen ist die automatische und schnelle semantische 3D-Modellierung der Umgebung eine wichtige Fragestellung in der Robotik. 3D-Laserscanner sind eine junge Technologie, die die Erfassung räumlicher Daten revolutioniert und Robotern das dreidimensionale Abtasten von Objekten möglich macht. Die vorliegende Arbeit untersucht und evaluiert mit Hilfe eines 3D-Laserscanners und des mobilen Roboters Kurt3D die zur automatischen semantischen 3D-Kartenerstellung notwendigen Algorithmen.
Der erste Teil der Arbeit beschäftigt sich mit der Aufgabe, 3D-Scans in einem globalen Koordinatensystem zu registrieren. Korrekte, global konsistente Modelle entstehen durch einen 6D-SLAM Algorithmus. Hierbei werden 6 Freiheitsgrade in der Roboterpose berücksichtigt, geschlossene Kreise erkannt und der globale Fehler minimiert. Die Basis des 6D-SLAM ist ein sehr schneller ICP-Algorithmus. Im zweiten Teil geht es darum, die Punktmodelle mit Semantik zu versehen. Dazu werden 3D-Flächen in einer digitalisierten 3D-Szene detektiert und interpretiert. Anschliessend sucht ein effizienter Algorithmus nach Objekten und bestimmt deren Pose, ebenfalls mit 6 Freiheitsgraden. Schliesslich wird der in den zahlreichen Experimenten verwendete, mobile Roboter Kurt3D vorgestellt.

Abstract: Intelligent autonomous acting in unstructured environments requires 3D maps with labelled 3D objects. 3D maps are necessary to avoid collisions with complex obstacles and to self localize in six degrees of freedom (x-, y-, z-position, roll, yaw and pitch angle). Meaning becomes inevitable, if the robot has to interact with its environment. The robot is then able to reason about the objects; its knowledge becomes inspectable and communicable. These arguments lead to requiring automatic and fast semantic environment modelling in robotics. A revolutionary method for gaging environments are 3D scanners, which enable robots to scan objects in a non-contact way in three dimensions. The presented work examines and evaluates the algorithms needed for automatic semantic 3D map building using a 3D laser range finder and the mobile robot Kurt3D.
The first part deals with the task to register 3D scans in a common coordinate system. Correct, globally consistent models result from a 6D SLAM algorithm. Hereby 6 degrees of freedom of the robot pose are considered, closed-loops are detected and the global error is minimized. 6D SLAM is based on a very fast ICP algorithm. In the second part semantic descriptions are derived from the point model. For that purpose 3D planes are detected and interpreted in the digitalized 3D scene. After that an efficient algorithm detects objects and estimates their pose with 6 degrees of freedom, too. Finally, the mobile robot Kurt3D, that was used in numerous experiments is presented.

Andreas Nüchter, Kai Lingemann and Oliver Wulf (Eds.). Robotic 3D Environment Cognition, Workshop at the International Conference Spatial Cognition, Bremen, Germany 2006, [Get Workshop Proceedings (PDF)].

A fundamental problem in the design of autonomous mobile cognitive systems is the perception of the environment. Robotics researches this field in order to build reliable technical systems or to broaden the understanding of human perception. Perception is therefore studied independently by many researchers. On one hand, a basic part of the perception is to learn, detect and recognize objects, which has to be done with the limited resources of a mobile robot. The performance of a mobile system crucially depends on the accuracy, duration and reliability of its perceptions and the involved interpretation process. On the other hand, automatic environment sensing and modeling is a fundamental scientific issue in robotics, since the availability of maps is essential for many robot tasks.
A revolutionary method for gaging surroundings are 3D laser range finders and 3D cameras, which enable robots to quickly scan objects in a non-contact way in three dimensions. These emerging technologies have lead to new challenges and new potentials for data analysis. Firstly, robotic volumetric or 3D mapping of environments, considering all six degree of freedom of a mobile robot, has been done. Secondly, robots are able to perceive the geometry for avoiding collision in 3D and to identify and stay on navigable surfaces. In addition, 3D sensors have lead to new methods in object detection, object localization and identification.

Kurt Konolige and Andreas Nüchter. Range Sensors. in: Bruno Siciliano, Oussama Khatib (eds.): Springer Handbook of Robotics, 2nd ed., Chapter 31. Springer, 2016

Summary: Range sensors are devices that capture the 3D structure of the world from the viewpoint of the sensor, usually measuring the depth to the nearest surfaces. These measurements could be at a single point, across a scanning plane, or a full image with depth measurements at every point. The benefits of this range data is that a robot can be relatively certain where the real world is, relative to the sensor, thus allowing the robot to more reliably find navigable routes, avoid obstacles, grasp objects, act on industrial parts, etc.
This chapter introduces the main representations for range data (point sets, triangulated surfaces, voxels), the main methods for extracting usable features from the range data (planes, lines, triangulated surfaces), the main sensors for acquiring it (Section 31.1 - stereo and laser triangulation and ranging systems), how multiple observations of the scene, e.g. as if from a moving robot, can be registered (Section 31.3) and several indoor and outdoor robot applications where range data greatly simplifies the task (Section 31.4).

Joachim Hertzberg, Kai Lingemann, Christopher Lörken, Andreas Nüchter, and Stefan Stiene. Does it help a robot navigate to call navigability an affordance?. In Towards Affordance-Based Robot Control. Proceedings of Dagstuhl Seminar 06231, Dagstuhl Castle, Germany, June 5-9, 2006, Springer (LNAI vol. 4760), ISBN 978-3-540-77914-8, pp. 16-26, 2008. [Get Paper] [Springer Link]

Abstract: Gibson's notion of affordance seems to attract roboticists' attention. On a phenomenological level, it allows functions, which have "somehow" been implemented, to be described using a new terminology. However, that does not mean that the affordance notion is of help for building robots and their controllers. This paper explores viewing an affordance as an abstraction from a robot-environment relation that is of inter-individual use, but requires an individual implementation. Therefore, the notion of affordance helps share environment representations and theories among robots. Examples are given for navigability, as afforded by environments of different types to robots of different undercarriages and sensor configurations.

Long Chen, Lei Fan, Guodong Xie, Kai Huang, and Andreas Nüchter, Moving-Object Detection From Consecutive Stereo Pairs Using Slanted Plane Smoothing, in IEEE Transactions on Intelligent Transportation Systems , vol.PP, no.99, pp.1-10, 2017. doi: 10.1109/TITS.2017.2680538, [Get Paper].

Abstract: Detecting moving objects is of great importance for autonomous unmanned vehicle systems, and a challenging task especially in complex dynamic environments. This paper proposes a novel approach for the detection of moving objects and the estimation of their motion states using consecutive stereo image pairs on mobile platforms. First, we use a variant of the semi-global matching algorithm to compute initial disparity maps. Second, assisted by the initial disparities, boundaries in the image segmentation produced by simple linear iterative clustering are classified into coplanar, hinge, and occlusion. Moving points are obtained during ego-motion estimation by a modified random sample consensus) algorithm without resorting to time-consuming dense optical flow. Finally, the moving objects are extracted by merging superpixels according to the boundary types and their movements. The proposed method is accelerated on the GPU at 20 frames per second. The data which we use for testing and benchmarking is released, thus completing similar data sets. It includes 812 image pairs and 924 moving objects with ground truth for better algorithms evaluation. Experimental results demonstrate that the proposed method achieves competitive results in terms of moving-object detection and their motion state estimation in challenging urban scenarios.

Keith Y. K. Leung, Daniel Lühr, Hamidreza Houshiar, Felipe Inostroza, Dorit Borrmann, Martin Adams, Andreas Nüchter, and Javier Ruiz del Solar. El Teniente Underground Mine Dataset. International Journal of Robotics Research (IJRR), volume 36, issue 1, pages 16-23, January 2017, [Get Paper].

Abstract: This article presents a robotic dataset collected from El Teniente, the largest copper mine in the world. Sensor measurements from a 3D scanning lidar, a 2D radar, and stereo cameras were recorded from an approximately two kilometer traverse of a production-active tunnel. The equipment used and the data collection process are discussed in detail, along with the format of the data. This dataset is suitable for research in robotic navigation, as well as simultaneous localization and mapping (SLAM). Download instructions are available at the website http://dataset.amtc.cl.

Rainer Koch, Stefan May, Patrick Murmann, and Andreas Nüchter. Identification of Transparent and Specular Reflective Material in Laser Scans to Discriminate Affected Measurements for Faultless Robotic SLAM. Journal of Robotics and Autonomous Systems (JRAS), Elsevier Science, ISSN 0921-8890, Vol. 87, pages 296-312, 2017, [Get Paper].

Abstract: Mapping with laser scanners is the state-of-the-art method applied in service, industrial, medical, and rescue robotics. Although a lot of research has been done, maps still suffer from interferences caused by transparent and specular reflective objects. Glass, mirrors, shiny or translucent surfaces cause erroneous measurements depending on the incident angle of the laser beam. In past experiments the Mirror Detector Approach was implemented to determine such measurements with a multi-echo laser scanner. Recognition values are based on its differences in recorded measurements in regard to the distance of the echoes. This paper describes the research to distinguish between reflective and transparent objects. The implemented Mirror Detector was specifically modified for recognition of said objects for which four experiments were conducted; one experiment to show the map of the original Mirror Detector; two experiments to investigate intensity characteristics based on angle, distance, and material; and one experiment to show an applied discrimination with the extended version of the Mirror Detector, the Reflection Classifier Approach. To verify the results, a comparison with existing models was performed. This study showed that shiny metals, like aluminum, etc., provide significant characteristics, while mirrors are to be characterized by a mixed model of glass and shiny metal. Transparent objects turned out to be challenging because their appearance in the sensor data strongly depends on the background. Nevertheless, these experiments show that discrimination of transparent and reflective materials based on the reflected intensity is possible and feasible.

Ville V. Lehtola, Juho-Pekka Virtanen, Matti T. Vaaja, Hannu Hyyppä, and Andreas Nüchter. Localization of a Mobile Laser Scanner via Dimensional Reduction. Volume 121, pages 48-59,ISSN 0924-2716, Elsevier, ISPRS Journal of Photogrammetry and Remote Sensing (JPRS), November 2016.

Abstract: We extend the concept of intrinsic localization from a theoretical one-dimensional (1D) solution onto a 2D manifold that is embedded in a 3D space, and then recover the full six degrees of freedom for a mobile laser scanner with a simultaneous localization and mapping algorithm (SLAM). By intrinsic localization, we mean that no reference coordinate system, such as global navigation satellite system (GNSS), nor inertial measurement unit (IMU) are used. Experiments are conducted with a 2D laser scanner mounted on a rolling prototype platform, VILMA. The concept offers potential in being extendable to other wheeled platforms.

Philipp Koch, Stefan May, Michael Schmidpeter, Markus Kühn, Christian Pfitzner, Christian Merkl, Rainer Koch, Martin Fees, Jon Martin, and Andreas Nüchter. Multi-Robot Localization and Mapping based on Signed Distance Functions, Journal Intelligent Robot Systems, ISSN 0921-0296, Springer, Volume 83, Issue 3, pp. 409-428, September 2016, [Get Paper].

Abstract: This publication describes a 2D Simultaneous Localization and Mapping approach applicable to multiple mobile robots. The presented strategy uses data of 2D LIDAR sensors to build a dynamic representation based on Signed Distance Functions. Novelties of the approach are a joint map built in parallel instead of occasional merging of smaller maps and the limited drift localization which requires no loop closure detection. A multi-threaded software architecture performs registration and data integration in parallel allowing for drift-reduced pose estimation of multiple robots. Experiments are provided demonstrating the application with single and multiple robot mapping using simulated data, public accessible recorded data, two actual robots operating in a comparably large area as well as a deployment of these units at the Robocup rescue league.

Janusz Bedkowski Karol Majek, Piotr Majek, Pawel Musialik, Michal Pelka, and Andreas Nüchter. Intelligent Mobile System for Improving Spatial Design Support and Security Inside Buildings, Mobile Networks and Applications. Volume 20, Issue 6, pages 1-14; doi:10.1007/s11036-015-0654-8, ISSN 1383-469X, Springer, 2015. [Get Paper].

Abstract: This paper concerns an intelligent mobile application for spatial design support and security domain. Mobility has two aspects in our research: The first one is the usage of mobile robots for 3D mapping of urban areas and for performing some specific tasks. The second mobility aspect is related with a novel Software as a Ser- vice system that allows access to robotic functionalities and data over the Ethernet, thus we demonstrate the use of the novel NVIDIA GRID technology allowing to virtualize the graphic processing unit. We introduce Complex Shape Histogram, a core component of our artificial intelligence engine, used for classifying 3D point clouds with a Support Vector Machine. We use Complex Shape Histograms also for loop closing detection in the simultaneous localization and mapping algorithm. Our intelligent mobile system is built on top of the Qualitative Spatio-Temporal Representa- tion and Reasoning framework. This framework defines an ontology and a semantic model, which are used for building the intelligent mobile user interfaces. We show experiments demonstrating advantages of our approach. In addition, we test our prototypes in the field after the end-user case studies demonstrating a relevant contribution for future intelligent mobile systems that merge mobile robots with novel data centers.

Helge A. Lauterbach, Dorit Borrmann, Robin Heß, Daniel Eck, Klaus Schilling, and Andreas Nüchter. Evaluation of a Backpack-Mounted 3D Mobile Scanning System, Remote Sensing. 7(10), 13753-13781; doi:10.3390/rs71013753, 2015. [Get Paper].

Abstract: Recently, several backpack-mounted systems, also known as personal laser scanning systems, have been developed. They consist of laser scanners or cameras that are carried by a human operator to acquire measurements of the environment while walking. These systems were first designed to overcome the challenges of mapping indoor environments with doors and stairs. While the human operator inherently has the ability to open doors and to climb stairs, the flexible movements introduce irregularities of the trajectory to the system. To compete with other mapping systems, the accuracy of these systems has to be evaluated. In this paper, we present an extensive evaluation of our backpack mobile mapping system in indoor environments. It is shown that the system can deal with the normal human walking motion, but has problems with irregular jittering. Moreover, we demonstrate the applicability of the backpack in a suitable urban scenario.

Andreas Nüchter, Dorit Borrmann, Jan Elseberg, and David Redondo. A Backpack-Mounted 3D Mobile Scanning System. Allgemeine Vermessungs-Nachrichten (AVN), Volume 122, Issue 10, pages 301-307, ISSN 0002-5968, Wichmann Verlag, October 2015.

Abstract: Mobile laser scanning systems automate the acquisition of 3D point clouds of environments. The mapping systems are commonly mounted on cars or ships. This paper presents a mapping solution mounted on a backpack. A clever choice of hard- and software enables the system to generate 3D maps without using GPS (global positioning system) information and without relying on expensive IMU (inertial measurement unit) systems. Therefore, it enables flexible indoor mapping.
Mobile Laserscansysteme automatisieren die Aufnahme von 3D-Punktwolken zur Erfassung von Umgebungen. Die Kartierungssysteme werden üblicherweise auf Autos oder Schiffen montiert. In dieser Arbeit präsentieren wir eine Lsung, die sich auf einem Rucksack montieren lässt. Durch geschickte Auswahl von Hard- und Software kann das System 3D-Karten ohne GPS-Information und ohne teure inertiale Messsysteme erstellen. Daher ermglicht es flexibel Innenräume zu kartieren.

Johannes Schauer and Andreas Nüchter. Collision detection between point clouds using an efficient k-d tree implementation. Advanced Engineering Informatics, Elsevier, Volume 29, Issue 3, pages 440-458, August 2015. [Get Paper].

Abstract:
Context: An important task in civil engineering is the detection of collisions of a 3D model with an environment representation. Existing methods using the structure gauge provide an insufficient measure because the model either rotates or because the trajectory makes tight turns through narrow passages. This is the case in either automotive assembly lines or in narrow train tunnels.
Objective: Given two point clouds, one of the environment and one of a model and a trajectory with six degrees of freedom along which the model moves through the environment, find all colliding points of the environment with the model within a certain clearance radius.
Method: This paper presents two collision detection (CD) methods called kd-CD and kd-CD-simple and two penetration depth (PD) calculation methods called kd-PD and kd-PD-fast. All four methods are based on searches in a k-d tree representation of the environment. The creation of the k-d tree, its search methods and other features will be explained in the scope of their use to detect collisions and calculate depths of penetration.
Results: The algorithms are benchmarked by moving the point cloud of a train wagon with 2.5 million points along the point cloud of a 1144 meter long train track through a narrow tunnel with overall 18.92 million points. Points where the wagon collides with the tunnel wall are visually highlighted with their penetration depth. With a safety margin of 5 cm kd-PD-simple finds all colliding points on its trajectory which is sampled into 19392 positions in 77 seconds on a standard desktop machine of 1.6GHz.
Conclusion: The presented methods for collision detection and penetration depth calculation are shown to solve problems for which the structure gauge is an insufficient measure. The underlying k-d tree is shown to be an effective data structure for the required look-up operations.

Dorit Borrmann, Hamidreza Houshiar, Jan Elseberg, Andreas Nüchter, Falk Näth, Stephan Winkler. Das Framework Castle3D zur fortlaufenden semantischen 3D-Kartierung von archäologischen Ausgrabungsstätten. Allgemeine Vermessungs-Nachrichten (AVN), Wichmann Verlag, Volume 122, Issue 6-7, pages 233-246, 2015.

Abstract: Das 3D-Laserscanning ist Stand der Technik bei der Modellierung archäologischer Ausgrabungsstätten, historischer Anlagen und sogar ganzer Städte oder Landschaften. Die Dokumentation der Befunde auf einer Ausgrabungsstätte ist eine wesentliche archäologische Aufgabe. Ein automatisiertes System würde diesen Prozess beschleunigen und die Anzahl der Fehler auf ein Minimum reduzieren. Dieser Beitrag stellt einen neuen Ansatz in der Dokumentation industrieller Archäologie durch die Entwicklung einer standardisierten Herangehensweise an die computerunterstützte Dokumentation einer archäologischen Ausgrabungsstätte vor. Ausserdem wird eine Reihe von Tools zur Erfassung und Registrierung von 3D- Daten auf Ausgrabungsstätten vorgestellt, die den Hauptbestandteil der Arbeitskette abdecken. Ein effi­ zientes Werkzeug für die Visualisierung der erworbenen 3D-Punktwolken im 3D- und 2D-Modus wird zur Verfügung gestellt. Der Hauptzweck dieser Software ist es, Archäologen ein einfach zu bedienendes Tool für die semantische Kartierung vor Ort zu bieten. Es enthält Funktionen für die Auswahl und Kennzeich- nung von Funden. Jedes Label kann mit weiteren Informationen versehen werden. Diese Daten werden im XML-Format exportiert und dienen als Eingabe für andere Systeme und Datenbanken.

Mohammad Al-khawaldah and Andreas Nüchter. Enhanced frontier-based exploration for indoor environment with multiple robots, Advanced Robotics, Volume 29, Issue 10, pages 657-669, Taylor & Francis, ISSN 0169-1864, [Get Paper].

Abstract: In this paper, the exploration and map building of unknown environment by a team of mobile robots is intensively investigated. A new exploration technique is proposed to increase the exploration efficiency. In particular, the new technique has two main objectives: firstly, it aims at reducing the exploration time and the travelled distance by reducing the overlap which takes place when a certain area in the environment is explored by more than one robot. To achieve this, a new procedure to assign the next target location for each individual robot is proposed. And secondly, it aims at reducing computations complexity required by target selection and path planning tasks. More importantly, the proposed technique obviates the need for environment segmentation complex procedures which is adopted in some previous important research works. The new technique is intensively tested with different environments. The results showed the effectiveness of the proposed technique.

HamidReza Houshiar, Jan Elseberg, Dorit Borrmann, and Andreas Nüchter. A Study of Projections for Key Point Based Registration of Panoramic Terrestrial 3D Laser Scans, Journal of Geo-spatial Information Science, Volume 18, Issue 1, pages 11-31, Taylor & Francis, ISSN 1009-5020, [Get Paper].

Abstract: This paper surveys state of the art image features and descriptors for the task of 3D scan registration based on panoramic reflectance images. As modern terrestrial laser scanners digitize their environment in a spherical way, the sphere has to be projected to a two-dimensional image. To this end, we evaluate the equirectangular, the cylindrical, the Mercator, the rectilinear, the Pannini, the stereographic, and the z-axis projection. We show that the Mercator and the Pannini projection outperform the other projection methods.

Mohammad Al-khawaldah and Andreas Nüchter. Multi-Robot Cooperation for Efficient Exploration. Automatika - Journal for Control, Measurement, Electronics, Computing and Communications, ISSN 0005-1144, Volume 55, No 3, pages 276-286, 2014, [Get Paper]. [Get Paper].

Abstract: This paper addresses the problem of exploration of an unknown environment by developing effective exploration strategies for a team of mobile robots equipped with continuously rotating 3D scanner. The main aim of the new strategies is to reduce the exploration time of unknown environment. Unlike most of other published works, to save time, the laser scanners rotate and scan the environment while robots are in motion. Furthermore, the new strategies are able to explore large outdoor environments as a considerable reduction of the required computations, especially those required for path planning, have been achieved. Moreover, a new exploration strategy has been developed so that robots continuously replan the order to visit the remaining unexplored areas according to the new data (i.e. updated map) collected by the robot in question or by the other team members. The new extension led to further enhancement but with slightly higher computational costs. Finally, to assess our new exploration strategies with different levels of environment complexity, new set of experiments were conducted in environments where obstacles are distributed according to the Hilbert curve. The results of these experiments show the effectiveness of the proposed technique to effectively distribute the robots over the environment. More importantly we show how the optimal number of robots is related to the environment complexity.

Girum Demisse, Dorit Borrmann, and Andreas Nüchter. Interpreting Thermal 3D Models of Indoor Environments for Energy Efficiency. In Journal of Intelligent and Robotic Systems, Springer, ISSN 0921-0296, Volume 77, Issue 1, pages 55-72, January 2015, [Get Paper].

Abstract: In recent years 3D models of buildings are used in maintenance and inspection, preservation, and other building related applications. However, the usage of these models is limited because most models are pure representations with no or little associated semantics. In this paper we present a pipeline of techniques used for interior interpretation, object detection, and adding energy related semantics to windows of a 3D thermal model. A sequence of algorithms is presented for building the fundamental semantics of a 3D model. Among other things, these algorithms enable the system to differentiate between objects in a room and objects that are part of the room, e.g. floor, windows. Subsequently, the thermal information is used to construct a stochastic mathematical model - namely Markov Random Field - of the temperature distribution of the detected windows. As a result, the MAP (Maximum a posteriori) framework is used to further label the windows as either open, closed or damaged based upon their temperature distribution. The experimental results showed the robustness of the techniques. Furthermore, a strategy to optimize the free parameters is described, in cases where there is a sample training dataset.

Dorit Borrmann, Andreas Nüchter, Marija Dakulovic, Ivan Maurovic, Ivan Petrovic, Dinko Osmankovic, and Jasmin Velagic. A mobile robot based system for fully automated thermal 3D mapping. Advanced Engineering Informatics, Elsevier, ISSN 1474-0346, Volume 28, Issue 4, pages 425–440, October 2014, [Get paper].

Abstract: It is hard to imagine living in a building without electricity and a heating or cooling system these days. Factories and data centers are equally dependent on a continuous functioning of these systems. As beneficial as this development is for our daily life, the consequences of a failure are critical. Malfunctioning power supplies or temperature regulation systems can cause the close-down of an entire factory or data center. Heat and air conditioning losses in buildings lead to a large waste of the limited energy resources and pollute the environment unnecessarily. To detect these flaws as quickly as possible and to prevent the negative consequences constant monitoring of power lines and heat sources is necessary. To this end, we propose a fully automatic system that creates 3D thermal models of indoor environments.
The proposed system consists of a mobile platform that is equipped with a 3D laser scanner, an RGB camera and a thermal camera. A novel 3D exploration algorithm ensures efficient data collection that covers the entire scene. The data from all sensors collected at different positions is joined into one common reference frame using calibration and scan matching. In the post-processing step a model is built and points of interest are automatically detected. A viewer is presented that aids experts in analyzing the heat flow and localizing and identifying heat leaks. Results are shown that demonstrate the functionality of the system.

Qingquan Li, Long Chen, Ming Li, Shih-Lung Shaw, and Andreas Nüchter. A Sensor-Fusion Drivable-Region and Lane-Detection System for Autonomous Vehicle Navigation in Challenging Road Scenarios. IEEE Transactions on vehicular technology, 62(2):540-555, February 2014. [Get Paper]

Abstract: Autonomous vehicle navigation is challenging since various types of road scenarios in real urban environments have to be considered, especially when only perception sensors are used, without position information. This paper presents a novel real-time optimal-drivable-region and lane detection system for autonomous driving based on the fusion of Light Detection and Ranging (LIDAR) and vision data. Our system uses a multisensory scheme to cover the most drivable areas in front of the vehicle. We propose a feature-level fusion method for LIDAR and vision data and an optimal selection strategy for detection of the best drivable region. Then a conditional lane detection algorithm is selectively executed depending on an automatic classification of the optimal drivable region. Our system successfully handles both structured and unstructured roads. The results of several experiments are provided to demonstrate the reliability, effectiveness, and robustness of the system.

Jan Elseberg, Dorit Borrmann, and Andreas Nüchter. Algorithmic Solutions for Computing Precise Maximum Likelihood 3D Point Clouds from Mobile Laser Scanning Platforms, Remote Sensing. 5(11), 5871-5906; doi:10.3390/rs5115871, 2013. [Get Paper].

Abstract: Motivated by Mobile laser scanning puts high requirements on the accuracy of the positioning systems and the calibration of the measurement system. We present a novel algorithmic approach for calibration with the goal of improving the measurement accuracy of mobile laser scanners. We describe a general framework for calibrating mobile sensor platforms that estimates all configuration parameters for any arrangement of positioning sensors including odometry. In addition, we present a novel semi-rigid Simultaneous Localization and Mapping (SLAM) algorithm that corrects the vehicle position at every point in time along its trajectory, while simultaneously improving the quality and precision of the entire acquired point cloud. Using this algorithm the temporary failure of accurate external positioning systems or the lack thereof can be compensated for. We demonstrate the capabilities of the two newly proposed algorithms on a wide variety of data sets.

Andreas Nüchter, Jan Elseberg, and Dorit Borrmann. Automation in 3D Laser Scanning -- From an Automated Tripod towards Optimal 3D Point Clouds from Mobile Laser Scanning. GIM International, Volume 27, Number 9, September 2013, [Get Paper].

Abstract: Motivated by the increasing need of rapid characterization of environments in 3D, we designed a robot system that automates the work of an operator of terrestrial laser scanners. The built system enables to work without markers or targets and enables the surveyors to save more than 75% of the time spent in the field. Another impulse for developing the platform is the demand for a remote inspection tool. The robot is capable to survey remote sites or danger areas, such as plants, underground mines, tunnels and caves, or channels. The availability of the robotic platform further enables us to study mobile laser scan systems. Now, the system is ready to do the work.
This article details the mobile robot, before we present our software solution. The software consists of automatic, high-precise registration programs for terrestrial scans, i.e., bundle adjustment, and its extension to mobile mapping, which requires precise calibration and trajectory optimization. Our algorithms do not rely on features at any point.

Janusz Bedkowski, Karol Majek, and Andreas Nüchter. General Purpose Computing on Graphics Processing Units for Robotic Applications. Journal of Software Engineering for Robotics (JOSER), Volume 4, Number 1, pages 23-33, ISSN 2035-3928, 2013. [Get Paper (PDF)].

Abstract: This paper deals with research related with the improvements of state of the art algorithms used in robotic applications based on parallel computation. The main goal is to decrease the computational complexity of 3D cloud of points processing in such applications as: data filtering, normal vector estimation, data registration and calculation of point feature histogram. The presented results efficiently improve the existing implementations with minimal lost of accuracy. The main contribution is a regular grid decomposition originally implemented for nearest neighborhood search. This data structure is used almost for all presented methods, it provides an efficient method for decreasing the time of computation. The results are compared with well-known robotic frameworks such as PCL and 3DTK.

Jan Elseberg, Dorit Borrmann, Andreas Nüchter. One Billion Points in the Cloud - An Octree for Efficient Processing of 3D Laser Scans, ISPRS Journal of Photogrammetry & Remote Sensing (JPRS), Special issue on terrestrial 3D modelling, Elsevier Science, Volume 76, pp. 76-88, ISSN 0924-2716, February 2013 [Get Paper].

Abstract: Automated 3-dimensional modeling pipelines include 3D scanning, registration, data abstraction, and visualization. All steps in such a pipeline require the processing of a massive amount of 3D data, due to the ability of current 3D scanners to sample environments with a high density. The increasing sampling rates make it easy to acquire Billions of spatial data points. This paper presents algorithms and data structures for handling these data. We propose an efficient octree to store and compress 3D data without loss of precision. We demonstrate its usage for an exchange file format, fast point cloud visualization, sped-up 3D scan matching, and shape detection algorithms. We evaluate our approach using typical terrestrial laser scans.

Jan Elseberg, Stéphane Magnenat, Roland Siegwart, and Andreas Nüchter. Comparison of nearest-neighbor-search strategies and implementations for efficient shape registration. Journal of Software Engineering for Robotics (JOSER), Volume 3, Number 1, ISSN 2035-3928, pages 2-12, 2012. [Get Paper (PDF)].

Abstract: The iterative closest point (icp) algorithm is one of the most popular approaches to shape registration currently in use. At the core of icp is the computationally-intensive determination of nearest neighbors (NN). As of now there has been no comprehensive analysis of competing search strategies for NN. This paper compares several libraries for nearest-neighbor search (NNS) on both simulated and real data with a focus on shape registration. In addition, we present a novel efficient implementation of NNS via k-d trees as well as a novel algorithm for NNS in octrees.

Jan Elseberg, Dorit Borrmann, and Andreas Nüchter. Eine Milliarde 3D-Punkte mit Standardhardware verarbeiten – Processing One Billion 3D Points on a Standard Computer. Allgemeine Vermessungs-Nachrichten (AVN), AVN-Themenheft mit Beiträgen aus den 3D-Tagen Oldenburg 2011, pages 11 - 23, Volume 119, Number 1, January 2012.

Abstract: Dieser Beitrag stellt eine neue Implementation der Octree-Datenstruktur vor. Sie ermöglicht es, eine Milliarde 3D-Punkte in 8 GB Hauptspeicher exakt zu repräsentieren und effiziente Algorithmen zu implementieren. Der Octree gibt eine Hierarchie vor, die dazu verwendet werden kann, grosse Punktwolken zu inspizieren und flüssig in ihnen zu navigieren. Des Weiteren schlagen wir in diesem Artikel ein effizentes binäres Dateiformat für den Austausch von 3D-Scans vor.
Schlüsselbegriffe: 3D-Punktwolke, Octree, Baumartige Datenstrukturen, verlustfreie Datenkomprimierung

In this paper we describe a new implementation of the spatial data structure called octree. We present an encoding that is capable of storing one billion points in 8 GB memory. The octree imposes a hierachy that can be used to inspect and visualize large point clouds and to navigate smoothly in it. In addition, we propose an efficient file format for exchanging 3D scans.
Key words: 3D point cloud, octree, tree like data structures, lossless compression, file formats

Jochen Sprickerhof, Andreas Nüchter, Kai Lingemann, and Joachim Hertzberg. A Heuristic Loop Closing Technique for Large-Scale 6D SLAM. Automatika - Journal for Control, Measurement, Electronics, Computing and Communications, Special Issue with selected papers from the European Conference on Mobile Robots 2009, Volume 52, Number 3, 2011. [Get Paper (PDF)].

Abstract: This paper presents a novel heuristic for correcting scan pose estimations after loop closing in SLAM using 3D laser scans. Contrary to state of the art approaches, the built SLAM graph is sparse, and optimization is done without any iteration between the SLAM front and back end, yielding a highly efficient loop closing method.
Several experiments were carried out in an urban environment and evaluated against ground truth. The results are compared to other state of the art algorithms, proving the high quality, yet achieved faster by an order of magnitude.

Andreas Nüchter, Stanislav Gutev, Dorit Borrmann, and Jan Elseberg. Skyline-based Registration of 3D Laser Scans. Journal of Geo-spatial Information Science, Special Issue with selected papers from the 3D City Modeling and Applications Workshop. Volume 14, Number 2, pages 85-90, ISSN 1009-5020, Springer Verlag, June 2011, [Get Paper] [Springer Link].

Abstract: Acquisition and registration of terrestrial 3D laser scans is a fundamental task in mapping and modeling of cities in three dimensions. To automate this task marker-free registration methods are required. Based on the existence of skyline features this paper proposes a novel method. The skyline features are extracted from panoramic 3D scans and encoded as strings enabling the use of string matching for merging the scans. Initial results of the proposed method in the old city center of Bremen are presented.

Dorit Borrmann, Jan Elseberg, Kai Lingemann, and Andreas Nüchter. The 3D Hough Transform for Plane Detection in Point Clouds - A Review and A new Accumulator Design, Journal 3D Research, ISSN 2092-6731, Springer, Volume 2, Number 2, March 2011, [Get Paper (PDF)] [Springer Link].

Abstract: The Hough Transform is a well-known method for detecting para\-metrized objects. It is the de facto standard for detecting lines and circles in 2-dimensional data sets. For 3D it has attained little attention so far. Even for the 2D case high computational costs have lead to the development of numerous variations for the Hough Transform. In this article we evaluate different variants of the Hough Transform with respect to their applicability to detect planes in 3D point clouds reliably. Apart from computational costs, the main problem is the representation of the accumulator. Usual implementations favor geometrical objects with certain parameters due to uneven sampling of the parameter space. We present a novel approach to design the accumulator focusing on achieving the same size for each cell and compare it to existing designs.

Stanislav Serebryakov, Lev Stankewich, and Andreas Nüchter. Визуальная навигация с времяпролетной камерой (Visual SLAM with Time-of-Flight Camera). Научно-технический ОПТИЧЕСКИЙ ЖУРНАЛ (Journal of Optical Technology). Volume 77, Issue 10, ISSN 0030-4042, pages 51-55, November 2010,

Abstract: В статье представлена система визуальной навигации в реальном времени с использованием времяпролетной камеры без априорных знаний о сцене. Представлен спо соб комплексирования времяпролетной и оптической камеры. Рассмотрены методы повышения робастности локализации, учитывающие цветовую и пространственную информацию.
The article presents a visual navigation system in real time using the time-of-flight camera without a priori knowledge of the scene. A method for fusing time-of- flight and the optical camera and methods for increasing the robustness of localization, taking into account the color and spatial information is discussed.

Joachim Hertzberg, Kai Lingemann, Christopher Lörken, Andreas Nüchter, Stefan Stiene and Thomas Wiemann. 3D-Roboterkartenbau in Osnabrück, KI Künstliche Intelligenz: Themenschwerpunk Simultaneous Localization and Mapping (SLAM) Volume 24, Number 3, September 2010 [Get Paper (PDF)].

Zusammenfassung: Seit Herbst 2004 existiert die Arbeitsgruppe "Wissensbasierte Systeme" am Institut für Informatik der Universität Osnabrück. Eines ihrer Arbeitsthemen ist der Bau von Roboterkarten basierend auf 3D-Laserscans bei 6-dimensionalen Scanposen. Wir geben einen Überblick über die wichtigsten Ergebnisse dazu und über die Perspektive dieses Themas für die Zukunft.

Andreas Nüchter, Jan Elseberg, Peter Schneider, and Dietrich Paulus. Study of Parameterizations for the Rigid Body Transformations of The Scan Registration Problem, Journal Computer Vision and Image Understanding (CVIU), Elsevier Science, Volume 114, Issue 8, pp. 963-980, ISSN 1077-3142, August 2010. [Get Paper (PDF)] [Elsevier Link with supplementary content].

Abstract: The ICP (Iterative Closest Point) algorithm is the de facto standard for geometric alignment of three-dimensional models when an initial relative pose estimate is available. The basis of the algorithm is the minimization of an error function that takes point correspondences into account. Four closed-form solution methods are known for minimizing this function. This paper presents novel linear solutions to the scan registration problem, i.e., to the problem of putting and aligning 3D scans in a common coordinate system. We extend the methods for registering n-scans in a global and simultaneous fashion, such that the registration of the n-th scan influences all previous registrations in one step.

Martin Magnusson, Henrik Andreasson, Andreas Nüchter, and Achim J. Lilienthal. Automatic Appearance-Based Loop Detection from 3D Laser Data Using the Normal Distributions Transform, Journal of Field Robotics (JFR), Special Issue on Three-Dimensional Mapping, Volume 26, Issue 11-12, November - December, 2009 [Get Paper (PDF)].

Abstract: We propose a new approach to appearance-based loop detection for mobile robots, using 3D laser scans. Loop detection is an important problem in the SLAMdomain, and, because it can be seen as the problem of recognizing previously visited places, it is an example of the data association problem. Without a flat floor assumption, 2D laser-based approaches are bound to fail in many cases. Two of the problems with 3D approaches that we address in this paper are how to handle the greatly increased amount of data and how to efficiently obtain invariance to 3D rotations. We present a compact representation of 3D point clouds that is still discriminative enough to detect loop closures without false positives (i.e., detecting loop closure where there is none). A low false positive rate is very important because wrong data association could have disastrous consequences in a SLAM algorithm. Our approach uses only the appearance of 3D point clouds to detect loops and requires no pose information. We exploit the NDT surface representation to create feature histograms based on surface orientation and smoothness. The surface shape histograms compress the input data by two to three orders of magnitude. Because of the high compression rate, the histograms can be matched efficiently to compare the appearance of two scans. Rotation invariance is achieved by aligning scans with respect to dominant surface orientations. We also propose to use expectation maximization to fit a Gamma mixture model to the output similarity measures in order to automatically determine the threshold that separates scans at loop closures from non-overlapping ones. We discuss the problem of determining ground truth in the context of loop detection and the difficulties in comparing the results of the few available methods based on range information. Furthermore, we present quantitative performance evaluations using three real-world data sets, one of which is highly self-similar, showing that the proposed method achieves high recall rates (percentage of correctly identified loop closures) at low false positive rates in environments with different characteristics.

Stefan May, David Dröschel, Dirk Holz, Stefan Fuchs, Ezio Malis, Andreas Nüchter, and Joachim Hertzberg. 3D Mapping with Time-of-Flight Cameras. Journal of Field Robotics (JFR), Special Issue on Three-Dimensional Mapping, Volume 26, Issue 11-12, November - December, 2009 [Get Paper (PDF)].

Abstract: This article investigates the use of Time-of-Flight (ToF) cameras in mapping tasks for autonomous mobile robots, in particular in simultaneous localization and mapping (SLAM) tasks. While ToF cameras are in principle an attractive type of sensor for 3D mapping owing to their high rate of frames of 3D data, two features of them make them difficult as mapping sensors, namely, their restricted field of view and influences on the quality of range measurements by high dynamics in object reflectivity; in addition, currently available models suffer from poor data quality in a number of aspects. The paper first summarizes calibration and filtering approaches for improving accuracy, precision and robustness of ToF camera independent of their intended usage. Then, several ego motion estimation approaches are applied or adapted, respectively, in order to provide a performance benchmark for registering ToF camera data. As a part of this, an extension to the Iterative Closest Point (ICP) algorithm has been developed that increases the robustness under restricted field of view and under larger displacements. Using an indoor environment, the paper provides results from SLAM experiments using these approaches in comparison. It turns out that the application of ToF cameras is feasible to SLAM tasks, although this type of sensor has a complex error characteristic.

Simone Frintrop, Andreas Nüchter, Kai Pervölz, Hartmut Surmann, Sara Mitri, Joachim Hertzberg. Attentive Classification, International Journal of Applied Artificial Intelligence in Engineering Systems, ISSN 0975-3176, Vol. 1, Number 1, June 2009. [Get Paper (PDF)]

Abstract: In this paper, we present a two-step approach for object recognition based on principles of human perception: Attentive Classification. First, regions of interest are detected by a biologically motivated attention system. Second, these regions are analyzed by a fast classifier based on the Adaboost learning technique. Thus, the classification effort is restricted to a small data subset. The approach has two advantages over normal classification: First, the system becomes considerably faster, which is an important factor for real-time systems. Second, since the attention system is able to make use of top-down target-information, the combination of the systems yields a significant reduction of false detections for objects which are usually difficult to discriminate from the surrounding. We show the performance of the system in several experiments in robotic scenarios. The presented attentive classification system represents an important step towards effective general object recognition which is fast, robust and flexibly adaptable to a current task.

Andreas Nüchter. Parallel and Cached Scan Matching for Robotic 3D Mapping. Journal of Computing and Information Technology Processing (eCIT), Special Issue on Advanced Mobile Robotics, Volume 17, Number 1, ISSN 1330-1136, pages 51-65, March 2009 [Get Paper (PDF)] [eCIT site].

Abstract: Intelligent autonomous acting of mobile robots in unstructured environments requires 3D maps. Since manual mapping is a tedious job, automatization of this job is necessary. Automatic, consistent volumetric modeling of environments requires a solution to the simultaneous localization and map building problem (SLAM problem). In 3D this task is computationally expensive, since the environments are sampled with many data points with state of the art sensing technology. In addition, the solution space grows exponentially with the additional degrees of freedom needed to represent the robot pose. Mapping environments in 3D must regard six degrees of freedom to characterize the robot pose. This paper summarizes our 6D SLAM algorithm and presents novel algorithmic and technical means to reduce computation time, i.e., the data structure cached k-d tree and parallelization. The availability of multi-core processors as well as efficient programming schemes as OpenMP permit the parallel execution of robotics tasks.

Andreas Nüchter and Joachim Hertzberg. Towards Semantic Maps for Mobile Robots. Journal of Robotics and Autonomous Systems (JRAS), Special Issue on Semantic Knowledge in Robotics, Elsevier Science, Volume 56, Issue 11, ISSN 0921-8890, pages 915-926, 2008. [ScienceDirect Link] [Get Paper].

Abstract: Intelligent autonomous action in ordinary environments calls for 3D maps. 3D geometry is necessary for avoiding collision with complex obstacles and to self localize in six degrees of freedom (6 DoF) (x, y, z positions, roll, yaw, and pitch angles). Meaning, in addition to geometry, becomes inevitable if the robot is supposed to interact with its environment in a goal-directed way. A semantic stance enables the robot to reason about objects; it helps disambiguate or round off sensor data; and the robot knowledge becomes reviewable and communicable.
The paper describes an approach and a completed robot system for semantic mapping. The prime sensor is a 3D laser scanner. Individual scans are registered into a coherent 3D geometry map by 6D SLAM. Coarse scene features (e.g., walls, floors in a building) are determined by semantic labeling. More delicate objects are then detected by a trained classifier and localized. In the end, the semantic maps can be visualized for human inspection. We sketch the overall architecture of the approach, explain the respective steps and their underlying algorithms, give examples based on a working robot implementation, and discuss the findings.

Oliver Wulf, Andreas Nüchter, Joachim Hertzberg, and Bernardo Wagner. Benchmarking Urban Six-Degree-of-Freedom Simultaneous Localization and Mapping. Journal of Field Robotics (JFR), Wiley & Son, ISSN 1556-4959, Vol. 25, Issue 3, pages 148 - 163, March, 2008, [Get Paper] [Get Videos].

Abstract: Quite a number of approaches for solving the simultaneous localization and mapping (SLAM) problem exist by now. Some of them have recently been extended to mapping environments with six degrees of freedom (DoF) poses, yielding 6D SLAM approaches. To demonstrate the capabilities of the respective algorithms, it is common practice to present generated maps and successful loop closings in large outdoor environments. Unfortunately, it is non-trivial to compare different 6D SLAM approaches objectively, because ground truth data about the outdoor environments used for demonstration is typically unavailable. We present a novel benchmarking method for generating this ground truth data based on reference maps. The method is then demonstrated by comparing the absolute performance of some previously existing 6D SLAM algorithms which build a large urban outdoor map.

Dorit Borrmann, Jan Elseberg, Kai Lingemann, Andreas Nüchter and Joachim Hertzberg. Globally consistent 3D mapping with scan matching. Journal of Robotics and Autonomous Systems (JRAS), Elsevier Science, Vol. 56, Issue 2, ISSN 0921-8890, pages 130 - 142, February 2008, [ScienceDirect Link] [Get Paper] [Get Videos] [Addendum].

Abstract: A globally consistent solution to the simultaneous localization and mapping (SLAM) problem in 2D with three degrees of freedom (DoF) poses was presented by Lu and Milios [F. Lu, E. Milios, Globally consistent range scan alignment for environment mapping, Autonomous Robots 4 (April) (1997) 333-349]. To create maps suitable for natural environments it is however necessary to consider the 6DoF pose case, namely the three Cartesian coordinates and the roll, pitch and yaw angles. This article describes the extension of the proposed algorithm to deal with these additional DoFs and the resulting non-linearities. Simplifications using Taylor expansion and Cholesky decomposition yield a fast application that handles the massive amount of 3D data and the computational requirements due to the 6DoF. Our experiments demonstrate the functionality of estimating the exact poses and their covariances in all 6DoF, leading to a globally consistent map. The correspondences between scans are found automatically by use of a simple distance heuristic.

Andreas Nüchter, Kai Lingemann, Joachim Hertzberg, and Hartmut Surmann, 6D SLAM - 3D Mapping Outdoor Environments Journal of Field Robotics (JFR), Special Issue on Quantitative Performance Evaluation of Robotic and Intelligent Systems, Wiley & Son, ISSN 1556-4959, Vol. 24, Issue 8-9, pages 699 - 722, August - September, 2007, [Get Paper].

Abstract: 6D SLAM (Simultaneous Localization and Mapping) or 6D Concurrent Localization and Mapping of mobile robots considers six dimensions for the robot pose, namely, the x, y and z coordinates and the roll, yaw and pitch angles. Robot motion and localization on natural surfaces, e.g., driving outdoor with a mobile robot, must regard these degrees of freedom. This paper presents a robotic mapping method based on locally consistent 3D laser range scans. Iterative Closest Point (ICP) scan matching, combined with a heuristic for closed loop detection and a global relaxation method, results in a highly precise mapping system. A new strategy for fast data association, cached kd tree search, leads to feasible computing times. With no ground-truth data available for outdoor environments, point relations in maps are compared to numerical relations in uncalibrated aerial images in order to assess the metric validity of the resulting 3D maps.

Andreas Nüchter, Kai Lingemann and Joachim Hertzberg. 6D SLAM with Kurt3D, Robotics Today, Society of Manufacturing Engineers, First Quarter, Vol. 20, No. 1, ISSN 0193-6913, April, 2007, [Get Paper (PDF)].

Abstract: 6D SLAM (Simultaneous Localization and Mapping) or 6D Concurrent Localization and Mapping of mobile robots considers six dimensions for the robot pose, namely, the x, y and z coordinates and the roll, yaw and pitch angles. Robot motion and localization on natural surfaces, e.g., when driving with a mobile robot outdoor, must regard these degrees of freedom. 3D (6 DOF) scan matching, combined with a heuristic for closed loop detection and a global relaxation method, results in a highly precise mapping system for outdoor environments. The mobile robot Kurt3D is capable to run the mapping process with its on-board sensors and computers and is used to digitalize different environments. This paper summarizes our previous research.

Andreas Nüchter, Kai Lingemann, Joachim Hertzberg, Oliver Wulf, Bernardo Wagner, Kai Pervölz, Hartmut Surmann, Thomas Christaller. The RoboCup Rescue Team Deutschland1, KI – Künstliche Intelligenz No. 2, pp. 24 - 29, ISSN 0933-1875, May 2006. [Get Paper (PDF)]

Abstract: The RoboCup Rescue competition aims at boosting research in robots and infrastructure able to help in real rescue missions. The task is to find and report victims in areas of different grades of roughness, which are currently indoor. It challenges to some extreme the mobility of robot platforms as well as the autonomy of their control and sensor interpretation software. In the 2004 competition, the Kurt3D robot was introduced, the first participant capable of mapping its environment in 3D and self-localizing in all six degrees of freedom, i.e., x, y, z positions and roll, yaw and pitch angles. In 2005, we have upgraded the system with more sensors, with a focus on speeding up the algorithms, and we have started to develop a tracked robot platform to cooperate with Kurt3D. This paper gives an introduction to the competition in general and presents main contributions of our Deutschland1 RoboCup Rescue team.

Sandor P. Fekete, Rolf Klein, and Andreas Nüchter. Online searching with an autonomous robot, in Computational Geometry: Theory and Applications (CGTA) . Elsevier Science, Vol. 34, Issue 2, pp. 102-115, ISSN 0925-7721, May 2006 [Get Paper (PDF)].

Abstract: We discuss online strategies for visibility-based searching for an ob ject hidden behind a corner, using Kurt3D, a real autonomous mobile robot. This task is closely related to a number of well-studied problems. Our robot uses a threedimensional laser scanner in a stop, scan, plan, go fashion for building a virtual three-dimensional environment. Besides planning trajectories and avoiding obstacles, Kurt3D is capable of identifying objects like a chair. We derive a practically useful and asymptotically optimal strategy that guarantees a competitive ratio of 2, which differs remarkably from the well-studied scenario without the need of stopping for surveying the environment. Our strategy is used by Kurt3D, documented in a separate video.

Kai Lingemann, Hartmut Surmann, Andreas Nüchter, and Joachim Hertzberg. Verfahren zur Ermittlung der Position und Orientierung eines navigierenden Systems. Offenlegungsschrift DE 10 2004 015 111 A1 2005.10.20, Deutsches Patentamt. Offenlegungstag 20.10.2005 [Get Paper] [European Patent office]

Abstract: Bei dem Verfahren zur Ermittlung der Position und Orientierung eines autonom navigierenden Systems, beispielsweise eines Roboters, in einer Umgebung werden die Entfernung des in Fahrtrichtung vor den navigierenden System liegenden Bereichs der Umgebung bei Bewegung des navigierenden Systems abgetastet und die abgetasteten Entfernungspunkte mindestens zweier aufeinanderfolgender Abtastvorgänge als Entfernungsmesskurven in der Polardarstellung gespeichert. Anschliessend werden die Entfernungsmesskurven der beiden aufeinander folgenden Abtastvorgänge auf charakteristische merkmale wie z.B. Extremwerte untersucht. Danach werden die parameter von einender getrennt durchführbaren Translations- und Rotationstransformationen der einen Entfernungsmesskurve zur Ermittlungder zuordnung der charakteristischen Merkmale der trnasformierten Entfernungsmesskurve zu solchen der anderen Entfernungsmesskurve und die Position und Orientierung des navigierenden Systems anhand von dessen Position und dessen Orientierung zum Zeitpunkt des zeitlich ersten von zwei aufeinanderfolgenden Abtastungen sowie der ermittelten Parameter der Translation- und Rotationstransformation bestimmt.

Hartmut Surmann, Kai Pervölz, Andreas Nüchter, Kai Lingemann, Joachim Hertzberg, and Matthias Hennig. Simultaneous Mapping and Localization of Rescue Environments in it- Information Technology 47 (2005) 5, pages 282 - 291, Oldenbourg press, ISSN 1611-2776, October 2005. (Note: The paper is an extended version of the SSRR 2005 best paper awarded paper "Mapping of Rescue Environments with Kurt3D")

Simone Frintrop, Erich Rome, Andreas Nüchter, and Hartmut Surmann, A Bimodal Laser-Based Attention System. Journal Computer Vision and Image Understanding (CVIU), Special Issue on Attention and Performance in Computer Vision, Elsevier Science, 100(1-2):124-151, ISSN 1077-3142, October - November 2005.

Abstract: In this paper, we present a new bimodal attention system for robotic applications capable of processing data from different sensor modes simultaneously. Considering several sensor modalities is an obvious approach to regard a variety of ob ject properties. Nevertheless, conventional att ention systems only regard the processing of camera images. In contrast to these systems, the input data to our system is provided by a bimodal 3D laser scanner, mounted on top of an autonomous mobile robot. In a single 3D scan pass, the scanner yields range as well as reflectance data. Both dat a modes are illumination independent, yielding a robust approach that enables all day operation. Data from both laser modes are fed into our attention system built on principles of one of the standard models of visual attention by Koch & Ullman. The system computes conspicuities of both modes in parallel and fuses them into one saliency map. The focus of attention is directed to the most salient points in this map sequentially. We present results on recorded scans of indoor and outdoor scenes showing the respective advantages of the sensor modalities enabling the mode-specific detectio n of different ob ject properties. Furthermore, we show as an application of the attention system the recognition of ob jects for building semantic 3D maps of the robot's environment. Key words: visual attention, saliency detection, bimodal sensor fusion, 3D laser scanner

Kai Lingemann, Andreas Nüchter, Joachim Hertzberg, and Hartmut Surmann. High-Speed Laser Localization for Mobile Robots, Journal Robotics and Autonomous Systems (JRAS), Elsevier Science, 51(4):275-296, 2005 [ScienceDirect link] [Get Paper (PDF)].

Abstract: This paper describes a novel, laser-based approach for tracking the pose of a high-speed mobile robot. The algorithm is outstanding in terms of accuracy and computation time. The efficiency is achieved by a closed-form solution for the matching of two laser scans, the use of natural scan features and fast linear filters. The implemented algorithm is evaluated with the high-speed robot Kurt3D (4 m/s), and compared to standard scan matching methods in indoor and outdoor environments. Keywords: Localization; Pose tracking; Autonomous mobile robots; Scan matching; High-speed robotics.

Hartmut Surmann, Andreas Nüchter, Kai Lingemann, and Joachim Hertzberg. Kurt3D - An Autonomous Mobile Robot for Modelling the World in 3D, in ERCIM NEWS 55 : 24 - 25, ISSN 0926-4981, October 2003, [online article] [Get Magazine (PDF)] [Get Paper (PDF)].

Abstract: Kurt3D is an autonomous mobile robot equipped with a reliable and precise 3D laser scanner that digitalizes environments. High quality geometric 3D maps with semantic information are automatically generated after the exploration by the robot.

Hartmut Surmann, Andreas Nüchter, and Joachim Hertzberg. An autonomous mobile robot with a 3D laser range finder for 3D exploration and digitalization of indoor environments, Journal Robotics and Autonomous Systems (JRAS), Elsevier Science, Vol. 45, Issue 3-4, ISSN 0921-8890, pages 181 - 198, December 2003, [Get Paper (PDF)].

Abstract: Digital 3D models of the environment are needed in rescue and inspection robotics, facility managements and architecture. This paper presen ts an automatic system for gaging and digitalization of 3D indoor environments. It consists of an autonomous mobile robot, a reliable 3D laser range finder and three elaborated software modules. The first module, a fast variant of the Iterative Closest Points algorithm, registers the 3D scans in a common coordinate system and relocalizes the robot. The second module, a next best view planner, computes the next nominal pose based on the acquired 3D data while avoiding complicated obstacles. The third module, a closed-loop and globally stable motor controller, navigates the mobile robot to a nominal pose on the base of odometry and avoids collisions with dynamical obstacles. The 3D laser range finder acquires a 3D scan at this pose. The proposed method allows one to digitalize large indoor environments fast and reliably without any intervention and solves the SLAM problem. The results of two 3D digitalization experiments are presented using a fast octree-based visualization method. Keywords: Autonomous mobile robots; 3D laser range finder; Scan matching; Next best view planning; 3D digitalization; 3D gaging; Robot relocalization; SLAM

Oliver Struckmeier, Dorit Borrmann, Andreas Nüchter. Teach-In für die 3D-Scan Akquise mit einem Roboter. in Photogrammetrie Laserscanning Optische 3D-Messtechnik, Beiträge der Oldenburger 3D-Tage 2017, Jade Hochschule, pages 280-289, ISBN 978-3-87907-625-7, Wichmann Verlag, February 2017. [Get Paper].

Zusammenfassung: Die 3D-Erfassung einer kompletten Umgebung mittels 3D-Laserscanner stellt abhängig von der zu scannenden Umgebung und dem Scanner einen hohen Zeitaufwand für einen menschlichen Operator dar. Der Scanner muss an die einzelnen Scanpositionen bewegt und dort verortet werden. Mit steigender Qualität der Messung nimmt zudem die Dauer der einzelnen Scanvorgänge zu. In diesem Beitrag wird ein Teach-In Ansatz vorgestellt und evaluiert, der den manuellen Vorgang verkürzt. Dabei führt ein Roboter die vom Vermesser geplanten und eingespeicherten zeitintensiven Schritte automatisch durch und entlastet somit den Bediener.

Andreas Nüchter, Michael Bleier, Johannes Schauer, and Peter Janotta. Improving Google's Cartographer 3D Mapping by Continuous-Time SLAM, In Proceedings of the 6th ISPRS International Workshop 3D-ARCH 2017: "3D Virtual Reconstruction and Visualization of Complex Architectures", Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-2/W3, 543-549, Nafplio, Greece, March 2017, [Get Paper], [Get Paper].

Abstract: This paper shows how to use the result of Google's SLAM solution, called Cartographer, to bootstrap our continuous-time SLAM algorithm. The presented approach optimizes the consistency of the global point cloud, and thus improves on Google's results. We use the algorithms and data from Google as input for our continuous-time SLAM software. We also successfully applied our software to a similar backpack system which delivers consistent 3D point clouds even in absence of an IMU.

Michael Bleier and Andreas Nüchter. Low-cost 3D Laser Scanning in Air or Water Using Self-calibrating Structured Light, In Proceedings of the 6th ISPRS International Workshop 3D-ARCH 2017: "3D Virtual Reconstruction and Visualization of Complex Architectures", Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-2/W3, 105-112, Nafplio, Greece, March 2017, [Get Paper], [Get Paper].

Abstract: In-situ calibration of structured light scanners in underwater environments is time-consuming and complicated. This paper presents a self-calibrating line laser scanning system, which enables the creation of dense 3D models with a single fixed camera and a freely moving hand-held cross line laser projector. The proposed approach exploits geometric constraints, such as coplanarities, to recover the depth information and is applicable without any prior knowledge of the position and orientation of the laser projector. By employing an off-the-shelf underwater camera and a waterproof housing with high power line lasers an affordable 3D scanning solution can be built. In experiments the performance of the proposed technique is studied and compared with 3D reconstruction using explicit calibration. We demonstrate that the scanning system can be applied to above-the-water as well as underwater scenes.

Helge A. Lauterbach, Dorit Borrmann, and Andreas Nüchter. Towards Radiometrical Alignment of 3D Point Clouds, In Proceedings of the 6th ISPRS International Workshop 3D-ARCH 2017: "3D Virtual Reconstruction and Visualization of Complex Architectures", Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-2/W3, 419-424, Nafplio, Greece, March 2017, [Get Paper], [Get Paper].

Abstract: 3D laser scanners are typically not able to collect color information. Therefore coloring is often done by projecting photos of an additional camera to the 3D scans. The capturing process is time consuming and therefore prone to changes in the environment. The appearance of the colored point cloud is mainly effected by changes of lighting conditions and corresponding camera settings. In case of panorama images these exposure variations are typically corrected by radiometrical aligning the input images to each other. In this paper we adopt existing methods for panorama optimization in order to correct the coloring of point clouds. Therefore corresponding pixels from overlapping images are selected by using geometrically closest points of the registered 3D scans and their neighboring pixels in the images. The dynamic range of images in raw format allows for correction of large exposure differences. Two experiments demonstrate the abilities of the approach.

Rainer Koch, Stefan May, and Andreas Nüchter. Detection and Purging of Specular Reflective and Transparent Object Influences in 3D Range Measurements, In Proceedings of the 6th ISPRS International Workshop 3D-ARCH 2017: "3D Virtual Reconstruction and Visualization of Complex Architectures", Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-2/W3, 377-384, Nafplio, Greece, March 2017, [Get Paper], [Get Paper].

Abstract: 3D laser scanners are favoured sensors for mapping in mobile service robotics at indoor and outdoor applications, since they deliver precise measurements at a wide scanning range. The resulting maps are detailed since they have a high resolution. Based on these maps robots navigate through rough terrain, fulfil advanced manipulation, and inspection tasks. In case of specular reflective and transparent objects, e.g., mirrors, windows, shiny metals, the laser measurements get corrupted. Based on the type of object and the incident angle of the incoming laser beam there are three results possible: a measurement point on the object plane, a measurement behind the object plane, and a measurement of a reflected object. It is important to detect such situations to be able to handle these corrupted points. This paper describes why it is difficult to distinguish between specular reflective and transparent surfaces. It presents a 3D- Reflection-Pre-Filter Approach to identify specular reflective and transparent objects in point clouds of a multi-echo laser scanner. Furthermore, it filters point clouds from influences of such objects and extract the object properties for further investigations. Based on an Iterative-Closest-Point-algorithm reflective objects are identified. Object surfaces and points behind surfaces are masked according to their location. Finally, the processed point cloud is forwarded to a mapping module. Furthermore, the object surface corners and the type of the surface is broadcasted. Four experiments demonstrate the usability of the 3D-Reflection-Pre-Filter. The first experiment was made in a empty room containing a mirror, the second experiment was made in a stairway containing a glass door, the third experiment was made in a empty room containing two mirrors, the fourth experiment was made in an office room containing a mirror. This paper demonstrate that for single scans the detection of specular reflective and transparent objects in 3D is possible. It is more reliable in 3D as in 2D. Nevertheless, collect the data of multiple scans and post-filter them as soon as the object was bypassed should pursued. This is why future work concentrates on implementing a post-filter module. Besides, it is the aim to improve the discrimination between specular reflective and transparent objects.

Andreas Nüchter. Effiziente Speicherung großer Punktwolken - Datenstrukturen für Algorithmen für mobile und terrestrische Laserscansysteme. in Terrestrisches Laserscanning 2016, Beiträge zum 154. DVW-Seminar, Schriftenreihe des DVW, Band 85, Wißner Verlag, ISBN 978-3-95786-106-1, pages 105-120, November 2017, [Get Book].

Johannes Schauer, Janusz Bedkowski, Karol Majek, and Andreas Nüchter. Performance comparison between state-of-the-art point-cloud based collision detection approaches on the CPU and GPU. in Proceedings of the 4th IFAC Symposium on Telematics Applications (TA '16), Porto Alegre, Brazil, November 2016, [Get Paper].

Abstract: We present two fundamentally different approaches to detect collisions between two point clouds and compare their performance on multiple datasets. A collision between points happens if they are closer to each other than a given threshold radius. One approach utilizes the main CPU with a k-d tree datastructure to efficiently carry out fixed range searches around points in 3D while the other mainly executes on a GPU using a regular grid decomposition technique implemented in the CUDA framework. We will show how massively parallel 3D range searches on a grid based datastructure on a GPU performs similarly well as a tree based approach on the CPU with orders of magnitude less parallelization. We also show how each method scales with varying input sizes and how they perform differently well depending on the spatial structure of the input data.

Florian Leutert, Dorit Borrmann, Klaus Schilling, and Andreas Nüchter. Spatial projection of thermal data for visual inspection. In Proceedings of the 14th International Conference on Control, Automation, Robotics and Vision (ICARCV ’16), Phuket, Thailand, November 2016, [Get Paper].

Abstract: Since the advent of thermal imaging, devices with a high optical resolution that use detector arrays to capture the emitted radiance in the thermal infrared range of an entire scene simultaneously have developed as a standard in monitoring energy related. They have had a huge impact on the building industry and in manifacturing, where they are commonly used to monitor proecces that require stable temperature conditions. As beneficial as contactless measurements are, the subsequent localization of points of interest in the environment is often difficult. To overcome this problem we propose a portable system that combines thermal imaging with Augmented Reality (AR). The idea of the approach is to project the gathered temperature information back into the scene to facilitate visual inspection.

Ville Lehtola, Juho-Pekka Virtanen, Petri Rönnholm, Andreas Nüchter. LOCALIZATION CORRECTIONS FOR MOBILE LASER SCANNER USING LOCAL SUPPORT-BASED OUTLIER FILTERING. in Proceedings of the ISPRS Congress 2016, ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., Prague, Czech Republic, 2016, [Get Paper],

Abstract: Following the pioneering work introduced in [Lehtola et al., ISPRS J. Photogramm. Remote Sens. 99, 2015, pp. 25–29], we extend the state-of-the-art intrinsic localization solution for a single two-dimensional (2D) laser scanner from one into (quasi) three dimensions (3D). By intrinsic localization, we mean that no external sensors are used to localize the scanner, such as inertial measurement devices (IMU) or global navigation satellite systems (GNSS). Specifically, the proposed method builds on a novel concept of local support-based filtering of outliers, which enables the use of six degrees-of-freedom (DoF) simultaneous localization and mapping (SLAM) for the purpose of enacting appropriate trajectory corrections into the previous one-dimensional solution. Moreover, the local support-based filtering concept is platform independent, and is therefore prone to be widely generalizable. The here presented overall method is yet limited into quasi-3D by its inability to recover trajectories with steep curvature, but in the future, it may be further extended into full 3D.

Dorit Borrmann, Florian Leutert, Ivan Maurovic, Marija Seder, Andreas Nüchter. Automatische Grundrisserstellung mittels Laserscandaten. in Photogrammetrie Laserscanning Optische 3D-Messtechnik, Beiträge der Oldenburger 3D-Tage 2016, Jade Hochschule, pages 108-119, ISBN 978-3-87907-604-8, Wichmann Verlag, February 2016. [Get Paper].

Zusammenfassung: In den letzten Jahren haben sich Laserscanner zum Stand der Technik bei der Erstellung von Gebäudemodellen entwickelt. Im Gegensatz zur vergleichsweise kurzen Aufnahmezeit bei der eigentlichen Erfassung der Umgebung mit dem Scanner nimmt die Nachbearbeitung der Daten einen deutlich höheren Zeitanteil ein. Eine manuelle Datenanalyse ist zeitaufwändig und fehleranfällig. Dies erhöht den Bedarf an automatischen Verfahren zur quantitativen Erfassung und Charakterisierung von Umgebungen.
In diesem Beitrag präsentieren wir eine automatische Grundrisserstellung basierend auf dem 3D Toolkit (3DTK - www.threedtk.de). Nach der autonomen Akquise mit einem mobilen Roboter werden die Daten mittels des iterativen Verfahrens der nächsten Punkte (engl. Iterative Closest Point (ICP)) registriert. Anschließend erfolgt eine automatische Vektorisierung eines 2D-Schnitts der Umgebung basierend auf Verfahren aus der Bildverarbeitung. Der so erzeugte Grundriss dient als Grundlage für eine semantische Karte.

Christian Pfitzner, Stefan May and Andreas Nüchter. Neural Network-based Visual Body Weight Estimation for Drug Dosage Finding, In Proceedings of the SPIE 9784, Medical Imaging 2016: Image Processing, doi:10.1117/12.2216042 San Diego, CA, USA, February 2016.

Abstract: Body weight adapted drug dosages are important for emergency treatments. This paper describes an improved body weight estimation approach for emergency patients in a trauma room, based on images from a RGBD sensor and a thermal camera. The improvements are archived by several extensions: The sensor fusion of RGBD and thermal camera eases filtering and segmentation of the patient's body from the background. Robustness and accuracy is gained by an artificial neural network (ANN), which considers features from the sensors as input to calculate the patient's body weight, e.g. the patient's volume, surface and shape parameters. The ANN is trained offline with 30 percent of the patients data. Preliminary experiments with 69 real patients show an accuracy close to 90 percent for a threshold of ten percent relative error in real body estimation. Results are compared to the patient's self estimation, a physician's guess and an anthropometric method: If the patient is knowledgeable it is the best possibility for body weight adapted drug dosages with 97 percent accuracy. The treating physicians and the anthropometric estimation achieve an accuracy of approximately 70 percent. The here presented approach gets an accuracy of nearly 90 percent and would be the best solution if a patient can not provide his own body weight and can not be weighted on a scale. These preliminary results demonstrate a sufficient approach for an upcoming clinical trial with 1,000 patients for body weight estimation.

Rainer Koch, Stefan May, Philipp Koch, Markus Kühn, and Andreas Nüchter. Detection of Specular Reflections in Range Measurements for Faultless Robotic SLAM, In Proceedings of ROBOT'2015: Second Iberian Robotics Conference, Lisbon, Portugal, Volume 417 of the series Advances in Intelligent Systems and Computing pp 133-145, 2015, [Get Paper].

Abstract: Laser scanners are state-of-the-art devices used for mapping in service, industry, medical and rescue robotics. Although a lot of work has been done in laser-based SLAM, maps still suffer from interferences caused by objects like glass, mirrors and shiny or translucent surfaces. Depending on the surface's reflectivity, a laser beam is deflected such that returned measurements provide wrong distance data. At certain positions phantom-like objects appear. This paper describes a specular reflectance detection approach applicable to the emerging technology of multi-echo laser scanners in order to identify and filter reflective objects. Two filter stages are implemented. The first filter reduces errors in current scans on the fly. A second filter evaluates a set of laser scans, triggered as soon as a reflective surface has been passed. This makes the reflective surface detection more robust and is used to refine the registered map. Experiments demonstrate the detection and elimination of reflection errors. They show improved localization and mapping in environments containing mirrors and large glass fronts is improved.

HamidReza Houshiar and Andreas Nüchter. 3D Point Cloud Compression using Conventional Image Compression for Efficient Data Transmission. In Proceedings of the XXV International Symposium on Information, Communication and Automation Technologies (ICAT '15), IEEE Xplore, Sarajevo, Bosnia, October 2015, [Get Paper (PDF)].

Abstract: Modern 3D laser scanners make it easy to collect large 3D point clouds. In this paper we present the use of conventional image based compression methods for 3D point clouds. We map the point cloud onto panorama images to encode the range, reflectance and color value for each point. An encoding method is presented to map the floating point measured ranges on to a three channel image. The image compression methods are used to compress the generated panorama images. We present the results of several lossless compression methods and the lossy JPEG on point cloud compression. Lossless compression methods are designed to retain the original data. On the other hand lossy compression methods sacrifice the details for higher compression ratio. This produces artefacts in the recovered point cloud data. We study the effects of these artefacts on encoded range data. A filtration process is presented for determination of range outliers from uncompressed point clouds.

Andreas Nüchter, Dorit Borrmann, Philipp Koch, Markus Kühn, Stefan May. A Man-Portable, IMU-free Mobile Mapping System. in Proceedings of the ISPRS Geospatial Week 2015, Laserscanning 2015, ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., II-3/W5, 17-23, La Grande Motte, France 2015, [Get Paper], [Get Paper],

Abstract: Mobile mapping systems are commonly mounted on cars, ships and robots. The data is directly geo-referenced using GPS data and expensive IMU (inertial measurement systems). Driven by the need for flexible, indoor mapping systems we present an inexpensive mobile mapping solution that can be mounted on a backpack. It combines a horizontally mounted 2D profiler with a constantly spinning 3D laser scanner. The initial system featuring a low-cost MEMS IMU was revealed and demonstrated at MoLaS: Technology Workshop Mobile Laser Scanning at Fraunhofer IPM in Freiburg in November 2014. In this paper, we present an IMU-free solution.

Hamidreza Houshiar, Dorit Borrmann, Jan Elseberg, Andreas Nüchter, Falk Näth, Stephan Winkler. CASTLE3D - A COMPUTER AIDED SYSTEM FOR LABELLING ARCHAEOLOGICAL EXCAVATIONS IN 3D. Proceedings of 25th CiPA Symposium, ISPRS Annals Photogrammetry and Remote Sensing Spatial Inf. Sci., II-5/W3, DOI 10.5194/isprsannals-II-5-W3-111-2015, pages 111-118, Taipei, Taiwan, September 2015. [Get Paper].

Abstract: Documentation of archaeological excavation sites with conventional methods and tools such as hand drawings, measuring tape and archaeological notes is time consuming. This process is prone to human errors and the quality of the documentation depends on the qualification of the archaeologist on site. Use of modern technology and methods in 3D surveying and 3D robotics facilitate and improve this process. Computer-aided systems and databases improve the documentation quality and increase the speed of data acquisition. 3D laser scanning is the state of the art in modelling archaeological excavation sites, historical sites and even entire cities or landscapes. Modern laser scanners are capable of data acquisition of up to 1 million points per second. This provides a very detailed 3D point cloud of the environment. 3D point clouds and 3D models of an excavation site provide a better representation of the environment for the archaeologist and for documentation. The point cloud can be used both for further studies on the excavation and for the presentation of results. This paper introduces a Computer aided system for labelling archaeological excavations in 3D (CASTLE3D). Consisting of a set of tools for recording and georeferencing the 3D data from an excavation site, CASTLE3D is a novel documentation approach in industrial archaeology. It provides a 2D and 3D visualisation of the data and an easy-to-use interface that enables the archaeologist to select regions of interest and to interact with the data in both representations. The 2D visualisation and a 3D orthogonal view of the data provide cuts of the environment that resemble the traditional hand drawings. The 3D perspective view gives a realistic view of the environment. CASTLE3D is designed as an easy-to-use on-site semantic mapping tool for archaeologists. Each project contains a predefined set of semantic information that can be used to label findings in the data. Multiple regions of interest can be joined under one label. Further information such as color, orientation and archaeological notes are added to the label to improve the documentation. The available 3D information allows for easy measurements in the data. The full 3D information of a region of interest can be segmented from the entire data. By joining this data from different georeferenced views the full 3D shape of findings is stored. All the generated documentation in CASTLE3D is exported to an XML format and serves as input for other systems and databases. Apart from presenting the functionalities of CASTLE3D we evaluate its documentation process in a sample project. For this purpose we export the data to the Adiuvabit database (http://adiuvabit.de) where more information is added for further analysis. The documentation process is compared to traditional documentation methods and it is shown how the automated system helps in accelerating the documentation process and decreases errors to a minimum.

Dorit Borrmann, Robin Hess, Daniel Eck, HamidReza Houshiar, Andreas Nüchter, and Klaus Schilling. Evaluation of Methods for Robotic Mapping of Cultural Heritage Sites, In Proceedings of the 2th IFAC conference on Embedded Systems, Computer Intelligence and Telematics (CESCIT '15), Maribor, Slovenia 2015,

Abstract: In archaeological studies the use of new technologies has moved into focus in the past years creating new challenges such as the processing of the massive amounts of data. In this paper we present steps and processes for smart 3D modelling of environments by use of the mobile robot Irma3D. A robot that is equipped with multiple sensors, most importantly a photo camera and a laser scanner, enables the automation of most of the processes, including data acquisition and registration. The robot was tested in the Würzburg Residence. Methods for automatic 3D color reconstructions of cultural heritage sites are evaluated in this paper.

Philipp Koch, Stefan May Michael Schmidpeter, Markus Kühn, Christian Pfitzner, Christian Merkl, Rainer Koch, Martin Fees, Jon Martin, and Andreas Nüchter. Multi-Robot Localization and Mapping based on Signed Distance Functions, Proceedings of the IEEE International Conference on Autonomous Robot Systems and Competitions (ICARSC '15), pages 77-82, Villa Real, Portugal, April 2015, [Get Paper].

Abstract: This publication describes a 2D Simultaneous Localization and Mapping approach applicable to multiple mobile robots. The presented strategy uses data of 2D LIDAR sensors to build a dynamic representation based on Signed Distance Functions. A multi-threaded software architecture performs registration and data integration in parallel allowing for drift-reduced pose estimation of multiple robots. Experiments are provided demonstrating the application with single and multiple robot mapping using simulated data, public accessible recorded data as well as two actual robots operating in a comparably large area.

Christian Pfitzner, Stefan May, Christian Merkl, Lorenz Breuer, Martin Köhrmann, Joel Braun, Franz Dirauf, and Andreas Nüchter. Libra3D: Body Weight Estimation for Emergency Patients in Clinical Environment with a 3D Structured Light Sensor, in Proceedings of the IEEE International Conference Robotics and Automation (ICRA '15), pages 2888 - 2893, Seattle, WA, USA, May 2015, [Get Paper].

Abstract: This paper describes the application of a weight estimation method for emergency patients in clinical environment. The approach applies established algorithms for point cloud processing and filtering on data from a low-cost structured light sensor. The patient's volume is estimated on the basis of his visible front surface. The approach is currently put to test in the workflow of the emergency room at the Universitätsklinikum Erlangen, Germany. Preliminary results show the accuracy of the approach in relation to other conservative means of weight measurements, like for example by physicians and anthropometric measurements.

Janis Gailis and Andreas Nüchter. Towards Globally Consistent Scan Matching With Ground Truth Integration, In Proceedings of the ISPRS International Conference on Photogrammetric Image Analysis (PIA '15), Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XL-3/W2, pages 59-64, Munich, Germany, March 2015, [Get Paper].

Abstract: The scan matching based simultaneous localization and mapping method with six dimensional poses is capable of creating a three dimensional point cloud map of the environment, as well as estimating the six dimensional path that the vehicle has traveled. The essence of it is the registering and matching of sequentially acquired 3D laser scans, while moving along a path, in a common coordinate frame in order to provide 6D pose estimations at the respective positions, as well as create a three dimensional map of the environment. An approach that could drastically improve the reliability of acquired data is to integrate available ground truth information. This paper is about implementing such functionality as a contribution to 6D SLAM (simultaneous localization and mapping with 6 DoF) in the 3DTK -- The 3D Toolkit software, as well as test the functionality of the implementation using real world datasets.

Dorit Borrmann, Robin Hess, Daniel Eck, Andreas Nüchter, and Klaus Schilling. Robotic Mapping of Cultural Heritage Sites, In Proceedings of the 5th ISPRS International Workshop 3D-ARCH 2015: "3D Virtual Reconstruction and Visualization of Complex Architectures", Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XL-5/W4, pages 9-16, Avila, Spain, February 2015, [Get Paper], [Get Paper].

Abstract: In archaeological studies the use of new technologies has moved into focus in the past years creating new challenges such as the processing of the massive amounts of data. In this paper we present steps and processes for smart 3D modelling of environments by use of the mobile robot Irma3D. A robot that is equipped with multiple sensors, most importantly a photo camera and a laser scanner, enables the automation of most of the processes, including data acquisition and registration. The robot was tested in two scenarios, Ostia Antica and the W\"urzburg Residence. The paper describes the steps for creating 3D color reconstructoins of these reknown cultural heritage sites.

Phil Käshammer and Andreas Nüchter. Mirror Identification and Correction of 3D Point Clouds, In Proceedings of the 5th ISPRS International Workshop 3D-ARCH 2015: "3D Virtual Reconstruction and Visualization of Complex Architectures", Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XL-5/W4,, Avila, Spain, February 2015, [Get Paper], [Get Paper].

Abstract: In terrestrial laser scanning (TLS), the surface geometry of objects is scanned by laser beams and recorded digitally. This produces a discrete set of scan points, commonly referred to as a point cloud. The coordinates of the scan points are determined by measuring the angles and the time-of-flight relative to the origin (scanner position). However, if it comes to mirror surfaces laser beams are fully reflected, due to the high reflectivity. Mirrors do not appear in the point cloud at all. Instead, for every reflected beam, a incorrect scan point is created behind the actual mirror plane. Consequently, problems arise in multiple derived application fields such as 3D virtual reconstruction of complex architectures. The paper presents a new approach to automatically detect framed rectangular mirrors with known dimensions and to correct the 3D point cloud, using the calculated mirror plane.

Stefan May, Philipp Koch, Rainer Koch, Christian Merkl, Christian Pfitzer, and Andreas Nüchter. A Gereralized 2D and 3D Multi-Sensor Data Integration Approach based on Signed Distance Functions for Multi-Modal Robotic Mapping. In Proceedings of th 19th International Workshop on Vision, Modeling and Visualization (VMV '14), Darmstadt, October 2014. [Get Paper] [Get Paper].

Abstract: This paper describes a data integration approach for arbitrary 2D/3D depth sensing units exploiting assets of the signed distance function. The underlying framework generalizes the KinectFusion approach with an object-oriented model respecting different sensor modalities. For instance, measurements of 2D/3D laser range finders and RGB-D cameras can be integrated into the same representation. Exemplary, an environment is reconstructed with a 3D laser range finder, while adding fine details from objects of interest by closer inspection with an \mbox{RGB-D} sensor. A typical application of this approach is the exploration in rescue environments, where large-scale mapping is performed on the basis of long-range laser range finders while hollows are inspected with lightweight sensors attached to a manipulator arm.

Johannes Schauer and Andreas Nüchter. Efficient Point Cloud Collision Detection and Analysis in a Tunnel Environment using Kinematic Laser Scanning and k-d Tree Search. In Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XL-3,, Proceedings of Photogrametric Computer Vision (PCV '14), pages 289-295, Zurich, September 2014. [Get Paper] [Get Paper] [Get Poster].

Abstract: Measuring the structure gauge of tunnels and other narrow passages has so far been the only way to evaluate whether large vehicles can pass through them. But especially for very long vehicles like train wagons and their cargo, the structure gauge is an insufficient measure because the center part of the vehicle between two bogies will inevitably leave the swept volume of its cross section when moving along any other trajectory than a straight line perpendicular to its cross section. In addition, the vehicle as well as the cargo must keep a minimum safety margin from the environment at all points of its trajectory. This paper explores an automated method to check for possible collisions of a model represented by a 3D point cloud moving through the 3D point cloud of an environment. We were given environment data of a train track through a narrow tunnel where simply relying on the structure gauge would indicate that a given wagon would pass through without any collision even though in reality, the train wagon would collide with the inner tunnel wall inside a sharp turn of the tracks. The k-d tree based collision detection method presented in this paper is able to correctly highlight these collisions and indicate the penetration depth of each colliding point of the environment into the model of the train wagon. It can be generalized for any setup where two static point clouds have to be tested for intersection along a trajectory.

Janusz Będkowski, Karol Majek, and Andreas Nüchter. Nowy algorytm 6DSLAM wykorzystujący semantyczne rozpoznanie otoczenia. 13 Krajowka Konferencja Robotyki Kudowa Zdrój Prace Naukowe, Elektronika z. 194 Post&ecedil;py Robotyki Tom II, pages 513-520, ISSN 0137-2343, July 2014. [Get Paper].

Abstract: W artykule przedstawiono modyfikację algorytmu 6DSLAM wykorzystującą semantyczne rozpoznawanie otoczenia. Zastosowanie semantycznego podejścia nie tylko poprawia w porównaniu do klasycznej metody dokładność tworzonej mapy metrycznej przez robota mobilnego, ale także umożliwia tworzenie takiej mapy w trudnych warunkach terenowych. Przedstawiono eksperymenty tworzenia mapy metrycznej/semantycznej budynków uwzględniając jazdę poziomą oraz kierunku pionowym po schodach. Porównano wynik z poprzednią implementacją algorytmu 6DSLAM. Nowe podejście poprawia spójność oraz dokładność mapy metrycznej. Zastosowanie semantycznego rozpoznawania otoczenia pozwala na rozszerzenie mapy metrycznej o nowe informacje o charakterze jakościowym, w tym przypadku rozróżniane są ściany, podłoga, sufit oraz punkty charakteryzujące się otoczeniem nieuporządkowanym.

Jan Elseberg, Dorit Borrmann, Johannes Schauer, Andreas Andreas Nüchter, Dirk Koriath, and Ulrich Rautenberg. A sensor skid for precise 3D modeling of production lines.. in ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., II-5, Proceedings of ISPRS Technical Commission V Symposium "Close-range imaging, ranging and applications", pages 117-122, June 2014. [Get Paper] [Get Paper]

Abstract: Motivated by the increasing need of rapid characterization of environments in 3D, we designed and built a sensor skid that automates the work of an operator of terrestrial laser scanners. The system combines terrestrial laser scanning with kinematic laser scanning and uses a novel semi-rigid SLAM method. It enables us to digitize factory environments without the need to stop production. The acquired 3D point clouds are precise and suitable to detect objects that collide with items moved along the production line.

HamidReza Houshiar, Dorit Borrmann, and Andreas Nüchter. Fortlaufende semantische 3D-Kartierung von archäologischen Ausgrabungsstätten. in Photogrammetrie Laserscanning Optische 3D-Messtechnik, Beiträge der Oldenburger 3D-Tage 2014, Jade Hochschule, Wichmann Verlag, ISBN 978-3-87907-536-2, pages 268-277, February 2014.

Zusammenfassung: Das 3D Laserscanning ist Stand der Technik bei der Modellierung archäologischer Ausgrabungsstätten, historischer Anlagen und sogar ganzer Städte oder Landschaften. Die Dokumentation der Befunde auf einer Ausgrabungsstätte ist eine wesentliche archäologische Aufgabe. Ein automatisiertes System würde diesen Prozess beschleunigen und die Anzahl der Fehler auf ein Minimum reduzieren. Dieser Beitrag stellt einen neuen Ansatz in der Dokumentation industrieller Archäologie vor. Er besteht aus einer Reihe von Tools zur Erfassung und Registrierung von 3D-Daten auf Ausgrabungsstätten. Wir stellen ein effizientes Werkzeug zur Verfügung für die Visualisierung der erworbenen 3D-Punktwolken im 3D- und 2D-Modus. Der Hauptzweck dieser Software ist Archäologen ein einfach zu bedienendes Tool für die semantische Kartierung vor Ort zu bieten. Es enthält Funktionen für die Auswahl und Kennzeichnung von Funden. Jedes Label kann mit weiteren Informationen versehen werden. Diese Daten werden im XML-Format exportiert und dienen als Eingabe für andere Systeme und Datenbanken.

Gerd Bruder, Frank Steinicke, and Andreas Nüchter. Immersive Point Cloud Virtual Environments.. in Proceedings of IEEE Symposium on 3D User Interfaces 3DUI Proceedings of IEEE Symposium on 3D User Interfaces (3DUI '14), Poster, pages 161-162, March 2014. [Get Paper]

Abstract: Today’s three-dimensional (3D) virtual environments (VEs) are usually based on textured polygonal 3D models, which represent the appearance and geometry of the virtual world. However, some application domains require other graphical paradigms, which are currently not adequately addressed by 3D user interfaces. We in- troduce a novel approach for a technical human-robot telepresence setup that allows a human observer to explore a VE, which is a 3D reconstruction of the real world based on point clouds. Such point cloud virtual environments (PCVEs) represent the external environ- ment, and are usually acquired by 3D scanners. We present an ap- plication scenario, in which a mobile robot captures 3D scans of a terrestrial environment, which are automatically registered to a co- herent PCVE. This virtual 3D reconstruction is displayed in an im- mersive virtual environment (IVE) in which a user can explore the PCVE. We explain and describe the technical setup, which opens up new vistas of presenting a VE as points rather than a polygonal representation.

Dorit Borrmann, HamidReza Houshiar, Jan Elseberg, Andreas Nüchter, Falk Näth, and Stephan Winkler. Fortlaufende semantische 3D-kartierung von archäologischen Ausgrabungsstätten. in Photogrammetrie Laserscanning Optische 3D-Messtechnik, Beiträge der Oldenburger 3D-Tage 2014, Jade Hochschule, Wichmann Verlag, February 2014.

Abstract: Das 3D Laserscanning ist Stand der Technik bei der Modellierung archäologischer Ausgrabungsstätten, historischer Anlagen und sogar ganzer Städte oder Landschaften. Die Dokumentation der Befunde auf einer Ausgrabungsstätte ist eine wesentliche archäologische Aufgabe. Ein automatisiertes System würde diesen Prozess beschleunigen und die Anzahl der Fehler auf ein Minimum reduzieren. Dieser Beitrag stellt einen neuen Ansatz in der Dokumentation industrieller Archäologie vor. Er besteht aus einer Reihe von Tools zur Erfassung und Registrierung von 3D-Daten auf Ausgrabungsstätten. Wir stellen ein effizientes Werkzeug zur Verfügung für die Visualisierung der erworbenen 3D-Punktwolken im 3D- und 2D-Modus. Der Hauptzweck dieser Software ist Archäologen ein einfach zu bedienendes Tool für die semantische Kartierung vor Ort zu bieten. Es enthält Funktionen für die Auswahl und Kennzeichnung von Funden. Jedes Label kann mit weiteren Informationen versehen werden. Diese Daten werden im XML-Format exportiert und dienen als Eingabe für andere Systeme und Datenbanken.

Girum G. Demisse, Dorit Borrmann, and Andreas Nüchter. Interpreting Thermal 3D Models of Indoor Environments for Energy Efficiency, Proceedings of the 16th IEEE International Conference on Advanced Robotics (ICAR '13), Montevideo, Urugauy, November 2013. [Get Paper].

Abstract: In recent years, 3D models of buildings are used in maintenance and inspection, preservation, and other building related applications. However, the usage of these models is limited, because most models are pure representations with no or little associated semantics. In this paper, we present a pipeline of techniques used for interior interpretation, object detection, and adding energy related semantics to windows of a 3D thermal model. A sequence of algorithms is presented for building the fundamental semantics of a 3D model. Furthermore, a Markov Random Field is used to model the temperature distribution of detected windows to further label the windows as either open, closed or damaged.

Billy Okal and Andreas Nüchter. Sliced Curvature Scale Space for Representing and Recognizing 3D objects, Proceedings of the 16th IEEE International Conference on Advanced Robotics (ICAR '13), Montevideo, Uruguay, November 2013. [Get Paper].

Abstract: Perception plays a key role in the development of intelligent autonomous systems. In particular object recognition and registration tasks are crucial to any intelligent autonomous system such as autonomous cars or personal robots. The repre- sentation of 3D object sensor measurements largely affects the choice of higher level processing possible on the sensor data. We explore the use of scale space theory via the curvature scale space and extend it to represent 3D objects in our new SCSS (Sliced Curvature Scale Space) framework. We further develop techniques of further processing the SCSS representation including feature extraction and dimensionality reduction for use in learning frameworks. We perform an array of experiments to validate the effectiveness of our method and demonstrate recognition performance using support vector machines. The results indicate that our new representation retains the nice qualities of the original curvature scale space method while being robust and compact for 3D object representation and recognition.

HamidReza Houshiar, Jan Elseberg, Dorit Borrmann, Andreas Nüchter. Panorama Based Point Cloud Reduction and Registration, Proceedings of the 16th IEEE International Conference on Advanced Robotics (ICAR '13), Montevideo, Urugauy, November 2013. [Get Paper].

Abstract: To reconstruct environments 3D point clouds acquired by laser scanners are registered. This is an important but also time consuming part of any mapping system for mobile robots. The time needed for mapping is drastically reduced when the size of the input data is reduced. This paper examines different ways of reducing the size of point clouds without losing vital information for the matching process. We present novel point cloud reduction methods on the basis of panorama images. It is shown that the reduced point clouds are ideally suited for feature based registration on panorama images. We evaluate the presented reduction methods based on their effect on the performance of the registration algorithm.

Andreas Nüchter, Jan Elseberg, and Dorit Borrmann, Irma3D - An Intelligent Robot for Mapping Applications, Proceedings of the 3rd IFAC Symposium on Telematics Applications (TA '13), Volume 3, Part 1, doi:10.3182/20131111-3-KR-2043.00011, Seoul, Korea, November 2013. [Get Paper].

Abstract: Motivated by the increasing need of rapid characterization of environments in 3D, we designed a robot system that automates the work of an operator of terrestrial laser scanners. The built system enables to work without using special targets or markers and thus enables the surveyors to save more than 75% of the time spent in the field. Another impulse for developing the platform is the demand for a remote multi-sensor inspection tool. The robot is capable of surveying remote sites or danger areas, such as plants, underground mines, tunnels, caves, or channels. The results are precise, multi-modal digital 3D maps.
This paper presents the recently developed robot Irma3D, its hardware, the developed interconnected software modules, the associated sensor calibration methods and a few applications.

Jan Elseberg, Dorit Borrmann, and Andreas Nüchter. A Study of Scan Patterns for Mobile Mapping, Proceedings of the ISPRS Conference on "Serving Society with Geoinformatics" (ISPRS-SSG '13), Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XL-7/W2, 75-80, doi:10.5194/isprsarchives-XL-7-W2-75-2013, Antalya, Turkey, November 2013, [Get Paper].

Abstract: Mobile terrestrial scanning systems automate terrestrial laser scanning. Continous scanning mobile terrestrial systems constantly spin the terrestrial laser scanner and thus combine terrestrial scanning with kinematic laser scanning. This paper presents a scan pattern analysis for these systems. We aim at finding the most advantageous combination of terrestrial and kinematic systems. The resulting 3D point cloud depends on the scan pattern and the trajectory and velocity of the mobile system.

HamidReza Houshiar, Jan Elseberg, Dorit Borrmann, Andreas Nüchter, Stephan Winkler, and Falk Näth. On-site Semantic Mapping of Archeological Excavation Areas, ISPRS Annals Photogrammetry and Remote Sensing. Spatial Inf. Sci., II-5/W1, 163-168, Strasbourg, France, September 2013, DOI 10.5194/isprsannals-II-5-W1-163-2013, [Get Paper]

Abstract: 3D laser scanning is the state of the art in modeling archaeological excavation sites, historical sites and even entire cities or landscapes. The documentation of findings on an excavation site is an essential archaeological task. Automated systems accelerate this process and decrease the amount of error to a minimum. This paper presents a new documentation approach in industrial archaeology. It consist of a set of tools for recording and registering 3D data from excavation sites. We provide an efficient tool for visualization of acquired 3D point clouds in 3D and 2D modes. The main purpose of this software is to provide an easy to use, on-site semantic mapping tool for archaeologist. It includes functions for selecting and labeling findings. Additional information can be provided for each label. This data is exported to an XML format and serves as input for other systems and data bases.

Corina Gurau and Andreas Nüchter. Challenges in Using Semantic Knowledge for 3D Object Classification, in Proceedings of the KI 2013 Workshop on Visual and Spatial Cognition, KIK - KI & Kognition Workshop Series, Koblenz, Germany, September 2013, [Get Paper].

Abstract: To cope with a wide variety of tasks, robotic systems need to perceive and understand their environments. In particular, they need a representation of individual objects, as well as contextual relations between them. Visual information is the primary data source used to make predictions and inferences about the world. There exists, however, a growing tendency to introduce high-level semantic knowledge to enable robots to reason about objects. We use the Semantic Web framework to represent knowledge and make inferences about sensor data, in order to detect and classify objects in the environment. The contribution of this work is the identification of several challenges that co-occur when combining sensor data processing with such a reasoning method.

Liang Zhang, Qingquan Li, Ming Li, Q.Zh Mao, and Andreas Nüchter. Multiple Vehicle-like Target Tracking Based on Velodyne Lidar, in Proceedings of the 6th IFAC Symposium on Intelligent Autonomous Vehicles (IAV '13), Volume 8, Part 1, DOI 10.3182/20130626-3-AU-2035.00058, Gold Coast, Australia, June 2013, [Get Paper].

Abstract: This paper proposes a novel Multiple vehicle-like target tracking method based on Velodyne HDL64E Lidar. The proposed method combines multiple hypothesis tracking (MHT) algorithm and dynamic point cloud registration (DPCR), which is able to solve the multiple vehicle-like target tracking in highly dynamic urban environments without any auxiliary information from GPS or IMU. Specifically, to track targets consistently, the DPCR is developed to calculate accurate location and pose of the ego-vehicle for the translation of raw measurements in moving coordinate systems into a static absolute coordinate system; while in turn, MHT helps to improve the performance of DPCR by discriminating and removing the dynamic points from the scene. Furthermore, the proposed MHT method is also able to solve the occlusion problem existing in the point cloud. Experiments on sets of urban environments prove that the presented method is effective and robust, even in highly dynamic environments.

Dorit Borrmann, Pedro J. de Rezende, Cid C. de Souza, Sandor P. Fekete, Stephan Friedrich, Alexander Kröller, Andreas Nüchter, Christiane Schmidt, and Davi C. Tozoni. Point Guards and Point Clouds: Solving general Art Gallery Problems. in Proccedings of the 29th ACM Annual Symposium on Computational Geometry (SoCG '13), pp. 347-348, ISBN 978-1-4503-2031-3, Rio de Janeiro, Brazil, June 2013. [Get Paper] [Get Video].

Abstract: In this video, we illustrate how one of the classical areas of computational geometry has gained in practical relevance, which in turn gives rise to new, fascinating geometric problems. In particular, we demonstrate how the robot platform IRMA3D can produce high-resolution, virtual 3D environments, based on a limited number of laser scans. Computing an optimal set of scans amounts to solving an instance of the Art Gallery Problem (AGP): Place a minimum number of stationary guards in a polygonal region P, such that all points in P are guarded.

Dorit Borrmann, HamidReza Houshiar, Jan Elseberg, and Andreas Nüchter. Vom Kombinieren von 3D-Modellen mit Farb- und Temperaturinformationen. in Photogrammetrie Laserscanning Optische 3D-Messtechnik, Beiträge der Oldenburger 3D-Tage 2013, Jade Hochschule, Wichmann Verlag, February 2013.

Zusammenfassung: In den letzten Jahren wurden große Fortschritte bei der automatischen Registrierung unterschiedlicher Daten gemacht, zum Beispiel bei Laserscandaten, Fotos und Thermalbilder. So wurden zuverlässige Methoden entwickelt, um Daten aus einem einzelnen Aufnahmeprozess zu registrieren. Probleme bereiten jedoch Daten, die zu unterschiedlichen Zeiten aufgenommen wurden. Dies ist aber essentiell um wertvolle Informationen verschiedener Sensoren zu kombinieren und den Anforderungen an die einzelnen Sensoren gerecht zu werden. Verwertbare Informationen von Thermalbildern erhält man ausschließlich ohne störende Einflüsse des Sonnenlichts. Farbfotos hingegen werden optimal bei guten Farbverhältnissen aufgenommen. Laserscanner sind relativ robust gegenüber wechselnden Lichtverhältnissen. Für alle Sensoren ist ein Aufnahmezeitpunkt wünschenswert, zu dem möglichst wenige dynamische Objekte die Szene beeinflussen. Üblicherweise ist eine genaue Georeferenzierung der Daten notwendig um Konsistenz zwischen den einzelnen Modellen zu erreichen. Dies erhöht den Aufwand für die Datenakquise erheblich. In diesem Beitrag präsentieren wir robuste Verfahren zur vereinfachten Kombination unterschiedlicher Datensätze.

Andreas Nüchter, Jan Elseberg, and Dorit Borrmann. Optimale 3D-Punktwolken aus mobilen Laserscandaten. in Photogrammetrie Laserscanning Optische 3D-Messtechnik, Beiträge der Oldenburger 3D-Tage 2013, Jade Hochschule, Wichmann Verlag, February 2013.

Zusammenfassung: Mobiles Laserscanning stellt hohe Anforderungen an die Exaktheit der Positionierung und Kalibrierung des Messsystems, da sich bereits kleinste Ungenauigkeiten in den akquirierten 3D-Daten drastisch niederschlagen können. Dieser Beitrag präsentiert eine neuen Ansatz zur Kalibrierung und zur Lösung des SLAM-Problems mit dem Ziel, die Messgenauigkeit des mobilen Scansystems zu optimieren. Bei dem Kalibrierungsverfahren handelt es sich um eine allgemeingültige Methode, die die Positionierung und Orientierung sämtlicher Sensoren berechnet, einschließlich der Odometrie. Der vorgestellte SLAM-Ansatz (Simultaneous Localization and Mapping) ist semi-rigide. Dabei wird die Trajektorie so deformiert und jede Pose dahingehend optimiert, dass die Gesamtqualität der 3D-Punktwolke optimal wird. Das SLAM-Verfahren kann kurzfristige Sensorausfälle oder Ungenauigkeiten ausgleichen und ermöglicht vielfältige neue Anwendungen.

Remus-Claudiu Dumitru, Dorit Borrmann, and Andreas Nüchter. Interior Reconstruction using the 3D Hough Transform, In Proceedings of the 5th ISPRS International Workshop 3D-ARCH 2013: "3D Virtual Reconstruction and Visualization of Complex Architectures", Trento, Italy, February 2013. [Get Paper (PDF)] [Archive Link] .

Abstract: Laser scanners are often used to create accurate 3D models of buildings for civil engineering purposes, but the process of manually vectorizing a 3D point cloud is time consuming and error-prone (A. Adan and D. Huber). Therefore, the need to characterize and quantify complex environments automatically arises, posing challenges for data analysis. This paper presents a system for 3D modeling by detecting planes in 3D point clouds, based on which the scene is reconstructed at a high architectural level through removing automatically clutter and foreground data. The implemented software detects openings, such as windows and doors, and completes the architectural model by inpainting.

Mihai-Cotizo Sima and Andreas Nüchter. An extension of the Felzenszwalb-Huttenlocher segmentation to 3D point clouds, In Proceedings of the 5th International Conference on Machine Vision (ICMV '12), SPIE 8783, Wuhan, China, October 2012, DOI 10.1117/12.2010527, (878302 (March 13, 2013)), [Get Paper].

Abstract: This paper investigates the segmentation algorithm proposed by Felzenszwalb and Huttenlocher and its compatibility to 3D point clouds acquired with state-of-the-art 3D laser scanners. To use the algorithm, we adapt the range and intensity data to the smoothed graph structure used by the algorithm. We investigate the influence of the algorithm's parameters to its performance and result that are meaningful to both the machines and the humans.

Jan Elseberg, Dorit Borrmann, Andreas Nüchter. 6DOF Semi-Rigid SLAM for Mobile Scanning, In Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS '12), ISBN 978-1-4673-1735-1, pages 1865 - 1870, Vilamoura/Algarve, Portugal, October 2012, [Get Paper].

Abstract: The terrestrial acquisition of 3D point clouds by laser range finders has recently moved to mobile platforms. Measuring the environment while simultaneously moving the vehicle demands a high level of accuracy from positioning systems such as the IMU, GPS and odometry. We present a novel semi-rigid SLAM algorithm that corrects the global position of the vehicle at every point in time, while simultaneously improving the quality and accuracy of the entire acquired map. Using the algorithm the temporary failure of positioning systems or the lack thereof can be compensated for. We demonstrate the capabilities of our approach on a wide variety of systems and data sets.

Dorit Borrmann, Hassan Afzal, Jan Elseberg, Andreas Nüchter. Video: Thermal 3D Modeling of Indoor Environments for Saving Energy, In Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS '12), ISBN 978-1-4673-1735-1, pages 4538 - 4539, Vilamoura/Algarve, Portugal, October 2012, [Get Paper].

Abstract: Heat and air conditioning losses in buildings and factories lead to a large amount of wasted energy. The Action Plan for Energy Efficiency [COM241] of the European Commission estimates that the largest cost-effective energy savings potential lies in residential (27) and commercial (30%) buildings. Imagine a technology that creates a precise digital 3D model of heat distribution and heat flow enabling one to detect all sources of wasted energy and to modify buildings to reach these savings. This video presents our approach to this task. Methods for creating a consistent laser scan model enhanced with information from thermal and optical cameras are presented.

Dorit Borrmann, Andreas Nüchter, Marija Dakulovic, Ivan Maurovic, Ivan Petrovic, Dinko Osmankovic, and Jasmin Velagic. The Project ThermalMapper – Thermal 3D Mapping of Indoor Environments for Saving Energy. In Proceedings of the 10th International IFAC Symposium on Robot Control (SYROCO '12), Volume 10, Part 1, ISBN 978-3-902823-11-3, DOI 10.3182/20120905-3-HR-2030.00045, Dubrovnik, Croatia, September 2012, [Get Paper (PDF)].

Abstract: Heat and air conditioning losses in buildings and factories lead to a large amount of wasted energy. The Action Plan for Energy Efficiency of the [COM241] estimates that the largest cost-effective energy savings potential lies in residential (≈ 27%) and commercial (≈ 30%) buildings. Imagine a technology that creates a precise digital 3D model of heat distribution and heat flow enabling one to detect all sources of wasted energy and to modify buildings to reach these savings. This paper presents our overall approach to map indoor environments with thermal data in 3D.

Dorit Borrmann, Hassan Afzal, Jan Elseberg, and Andreas Nüchter. Mutual Calibration for 3D Thermal Mapping. In Proceedings of the 10th International IFAC Symposium on Robot Control (SYROCO '12), Volume 10, Part 1, ISBN 978-3-902823-11-3, DOI 10.3182/20120905-3-HR-2030.00073, Dubrovnik, Croatia, September 2012, [Get Paper (PDF)].

Abstract: Three-dimensional digital heat distribution maps are needed to assess the energy efficiency of real estates. The availability of such maps are of great importance for reducing the ecological footprint of houses, buildings, and factories. Designing estates has reached the point, where so-called Passivhaus buildings make extensive use of the intrinsic heat from internal sources such as waste heat from lighting, white goods, and other electrical devices, but without using dedicated heaters. In our approach for creating high-precise heat distribution maps a robot is equipped with a 3D laser scanner, a thermal camera, and a color camera. Data from all the sensors are combined to model the environment precisely. This paper describes the setup of the sensors and the processing of the acquired data, including the automatic co-calibration needed to fulfill this task.

Stefan May, Rainer Koch, Robert Scherlipp, and Andreas Nüchter. Robust Registration of Narrow-Field-of-View Range Images. In Proceedings of the 10th International IFAC Symposium on Robot Control (SYROCO '12), Volume 10, Part 1, ISBN 978-3-902823-11-3, DOI 10.3182/20120905-3-HR-2030.00057, Dubrovnik, Croatia, September 2012, [Get Paper (PDF)].

Abstract: This paper focuses on range image registration for robot localization and environment mapping. It extends the well-known Iterative Closest Point (ICP) algorithm in order to deal with erroneous measurements. The dealing with measurement errors originating from external lighting, occlusions or limitations in the measurement range is only rudimentary in literature. In this context we present a non-parametric extension to the ICP algorithm that is derived directly from measurement modalities of sensors in projective space. We show how aspects from reverse calibration can be embedded in search-tree-based approaches. Experiments demonstrate the applicability to range sensors like the Kinect device, Time-of-Flight cameras and 3D laser range nders. As a result the image registration becomes faster and more robust.

Mohammad Al-khawaldah and Andreas Nüchter. Multi-Robot Exploration and Mapping with a rotating 3D Scanner. In Proceedings of the 10th International IFAC Symposium on Robot Control (SYROCO '12), Volume 10, Part 1, ISBN 978-3-902823-11-3, DOI 10.3182/20120905-3-HR-2030.00025, Dubrovnik, Croatia, September 2012, [Get Paper (PDF)].

Abstract: This paper investigates the field of exploration and map-building with multiple cooperating mobile robots. New and efficient exploration and mapping technique is proposed by employing laser scanners. The paper also aims to extend existing exploration and mapping techniques of single robot to multi-robot to increase the exploration efficiency (i.e. to reduce the environment exploration time and the energy consumed by the robots to accomplish the exploration task). The goal of the proposed method is to have multiple mobile robots exploring a given unknown environment as fast as possible, while coordinating their actions and sharing their local maps in certain time instances. In the suggested technique, each robot is equipped with a laser scanner that is continuously rotating to scan the environment, and is employing a frontier-based exploration algorithm which is important to guide the robots during the exploration. A new factor is introduced to enhance the performance of the frontier-based exploration. This factor aims at spreading robots in the environment to reduce overlap.

Dorit Borrmann, Jan Elseberg, and Andreas Nüchter. Thermal 3D Mapping of Building Façades. In Proceedings of the 12th Conference on Intelligent Autonomous Systems (IAS '12), ISBN 978-3-642-33931-8, Jeju Island, Korea, June 2012, [Get Paper (PDF)].

Abstract: Never before in history were humans as dependant on energy as we are today. But the natural ressources are limited and a waste of energy has drastic influences on the environment. In their Action Plan for Energy Efficiency [COM241] the European Commission estimates that the largest and cost-effictive energy savings potential lies in residential (≈27%) and commercial (≈30%) buildings. To eliminate heat and air conditioning losses in buildings and factories heat and air leaks need to be localized and identified. Imagine the availability of a complete 3D model of every building that architects can use to analyze the heat insulation of buildings and to identify necessary modifications. In these 3D models temperature peaks are not only detectable but also their extent is visible. A robot equiped with a 3D laser scanner, a thermal camera, and a color camera constitutes the basis for our approach. The data from all three sensors and from different locations are joined into one high-precise 3D model that shows the heat distribution. This paper describes the setup of the hardware and the methods applied to create the 3D model, including the automatic co-calibration of the sensors. Challenges unique to the task of thermal mapping of outdoor environments are discussed.

Jan Elseberg, Dorit Borrmann, and Andreas Nüchter. Automatic and Full Calibration of Mobile Laser Scanning Systems. In Proceedings of the 13th International Symposium of Experimental Robotics (ISER '12), Springer Tracts in Advanced Robotics, Vol. 79, ISBN 978-3-642-28571-4, Québec City, Canada, June 2012.

Abstract: Mobile scanning, i.e., the practice of mounting laser scanners on moving platforms is an efficient way to acquire accurate and dense 3D point clouds of outdoor environments for urban and regional planning and architecture. The mobile scenario puts high requirements on the accuracy of the calibration of the measurement system, as small calibration inaccuracies lead to large errors in the resulting point cloud. We propose a novel algorithm for the calibration of a mobile scanning system that estimates the calibration parameters for \emph{all} sensor components simultaneously without relying on additional hardware. We evaluate the calibration algorithm on several real world data sets where ground truth is available via an accurate geodetic model.

Long Chen, Qingquan Li, Quanwen Zhu, Ming Li, and Andreas Nüchter. 3D LIDAR Point Cloud based Intersection Recognition for Autonomous Driving. In 2012 IEEE Intelligent Vehicles Symposium (IV '12), ISBN 978-1-4673-2118-1, pages 456-461, Alcalá de Henares, Madrid, Spain, June 2012. [Get Paper (PDF)].

Abstract: Finding road intersections in advance is crucial for navigation and path planning of moving autonomous vehicles, especially when there is no position or geographic auxiliary information available. In this paper, we investigate the use of a 3D point cloud based solution for intersection and road segment classification in front of an autonomous vehicle. It is based on the analysis of the features from the designed beam model. First, we build a grid map of the point cloud and clear the cells which belong to other vehicles. Then, the proposed beam model is applied with a specified distance in front of autonomous vehicle. A feature set based on the length distribution of the beam is extracted from the current frame and combined with a trained classifier to solve the road-type classification problem, i.e., segment and intersection. In addition, we also make the distinction between +-shaped and T-shaped intersections. The results are reported over a series of real-world data. A performance of above 80% correct classification is reported at a real-time classification rate of 5 Hz.

Ming Li, Wei Li, Jian Wang, Qingquan Li, and Andreas Nüchter Dynamic VeloSLAM – Preliminary Report on 3D Mapping of Dynamic Environments. In 2012 IEEE Intelligent Vehicles Symposium (IV '12), Workshop on Navigation, Perception, Accurate Positioning and Mapping for Intelligent Vehicles, Alcalá de Henares, Madrid, Spain, June 2012 [Get Paper (PDF)].

Abstract: 3D mapping using point cloud registration is a basic inevitable problem for many applications, especially for modeling of large scale complicated environments. This paper presents a novel approach for mapping highly dynamic environments, i.e., we present a system capable for mapping road traffic scenarios. Given 3D laser scans acquired at a high frame rate and no other sensor input, a 3D map is built by removing dynamic parts of the scene and estimating the ego-motion of the vehicle precisely at the same time. We extend the well-known ICP algorithm for HDL-64 laser scan data and build a system for solving the simultaneous localization and mapping problem in urban road scenarios. This paper presents initial results on two data sets.

Girum Demisse, Razvan Mihalyi, Billy Okal, Dev Poudel, Johannes Schauer, and Andreas Nüchter, Mixed Palletizing and Task Completion for Virtual Warehouses. in Virtual Manufacturing Automation (VMAC '12) Workshop at IEEE International Conference Robotics and Automation, ICRA, 2012 [Get Paper (PDF)].

Abstract: Palletizing, or packing rectangular boxes of various sizes onto pallets, is a frequently encountered task in many commercial scenarios, e.g., shipment of goods. An extension of this problem is the automated placement of boxes on pallets, henceforth task completion, by means of industrial robot arms. The palletizing and task completion problems are treated in the context of the IEEE ICRA 2012 Virtual Manufacturing Automation Competition. We approach the palletizing challenge by a winner-takes-all strategy, where multiple heuristics are evaluated against the given datasets. Our results show a performance comparable to that of the commercial software benchmark from the previous competitions. We solve task completion in USARSim by picking boxes and placing them on a pallet. Our inverse kinematics algorithm consists of a geometric and numeric component.

Thomas Wiemann, Kai Lingemann, Andreas Nüchter, and Joachim Hertzberg. A Toolkit for Automatic Generation of Polygonal Maps – Las Vegas Reconstruction. in Proceedings of the 7th German Conference Robotik 2012, pages 446-451, VDE Verlag, ISBN 978-3-8007-3418-4, Munich, Germany, May 2012. [Get Paper (PDF)].

Abstract: In this paper we present a new open source software package for automatic generation of polygonal 3D maps from point cloud data for robotic purposes called "Las Vegas Reconstruction Toolkit" [11]. The implemented algorithms focus on minimizing the computational costs and optimization of the number of polygons in the generated maps. Furthermore, we present two application examples: 6D self localization and scene interpretation.

Dorit Borrmann, Jan Elseberg, Prashant Narayan K.C., and Andreas Nüchter. Ein Punkt pro Kubikmeter – präzise Registrierung von terrestrischen Laserscans mit Scanmatching. in Photogrammetrie Laserscanning Optische 3D-Messtechnik, Beiträge der Oldenburger 3D-Tage 2012, pages 4-11, Jade Hochschule, Wichmann Verlag, ISBN 978-3-87907-515-7, February 2012.

Zusammenfassung: Die präzise Registrierung von terrestrischen Laserscans erfordert geschultes Personal, professionelle Scanner Hardware, meist proprietäre Software sowie genügend Zeit für die Anbringung von Zielmarken, Durchführung der Messungen und die anschlie&szilg;ende Verarbeitung der akquirierten Daten. Wir zeigen, wie man auf einige dieser Punkte verzichten und dennoch zu hochqualitativen Ergebnissen kommen kann.
Im Zuge einer Bachelorarbeit wurde ein der Vermessungstechnik fremder Informatikstudent damit beauftragt, den Campus der Jacobs University auf einer Teilfläche von ca. 9 ha zu vermessen. Zur Verfügung standen ein professioneller Scanner in Form des Riegl VZ-400. Insgesamt wurden 131 Aufnahmen mit insgesamt über 2 Milliarden Punkten gemacht. Nach manueller Vorregistrierung der Punktwolken erfolgte die präzise Anordnung dann vollautomatisch mit der frei erhältlichen Software 3DTK, die dazu in der Lage war die gesamte Datenmenge in kürzester Zeit mit höchster Genauigkeit zu registrieren.

Andreas Nüchter, HamidReza Houshiar, Dorit Borrmann, and Jan Elseberg. Projektionen für die Scanregistrierung mit Hilfe von Bildmerkmalen. in Photogrammetrie Laserscanning Optische 3D-Messtechnik, Beiträge der Oldenburger 3D-Tage 2012, pages 12-21, Jade Hochschule, Wichmann Verlag, ISBN 978-3-87907-515-7, February 2012.

Zusammenfassung: Die Aufnahme und das Registrieren von terrestrischen 3D-Laserscans ist eine grundlegende Fragestellung in vielen Anwendungsbereichen. Um den Prozess des Registrierens von zwei 3D-Scans zu automatisieren, werden Merkmale aus den Scandaten extrahiert, diese einander zugeordnet (assoziiert) und die Registrierung berechnet. Als Merkmale kommen neben Strukturmerkmalen wie 3D-Flächen oft Bildmerkmale zum Einsatz. Dazu wird ein flächiges Bild der Reflektionswerte eines 3D-Scans erzeugt. In der Regel wird hierbei auf der x-Achse der Rotationswinkel um die Stehachse des Scanners und auf der y-Achse der Rotationswinkel des Spiegels abgetragen. In diesem Beitrag untersuchen wir wie sich die Registrierungsergebnisse ändern, wenn andere Projektionen verwendet werden. Dazu analysieren wir mit Hilfe von SIFT-Merkmalen die gleichmäßige Rektangularprojektion, die zylindrische Projektion, die Hochachsenrojektion, die Mercatorprojektion, die Rektangularprojektion, die Pannini-Projektion, sowie die stereographische Projektion.

Flavia Grosan, Alexandru Tandrau, Andreas Nüchter. Localizing Google SketchUp Models in Outdoor 3D Scans. In Proceedings of the XXIII International Symposium on Information, Communication and Automation Technologies (ICAT '11), IEEE Xplore, ISBN 978-1-4577-0746-9, Sarajevo, Bosnia, October 2011 [Get Paper (PDF)] [Get Video] [Get Video].

Abstract: This work introduces a novel solution for localizing objects based on search strings and freely available Google SketchUp models. To this end we automatically download and preprocess a collection of 3D models to obtain equivalent point clouds. The outdoor scan is segmented into individual objects, which are sequentially matched with the models by a variant of iterative closest points algorithm using seven degrees of freedom and resulting in a highly precise pose estimation of the object. An error function evaluates the similarity level. The approach is verified using various segmented cars and their corresponding 3D models.

Jan Elseberg, Dorit Borrmann, and Andreas Nüchter. Full Wave Analysis in 3D Laser Scans for Vegetation Detection in Urban Environments. In Proceedings of the XXIII International Symposium on Information, Communication and Automation Technologies (ICAT '11), IEEE Xplore, ISBN 978-1-4577-0746-9, Sarajevo, Bosnia, October 2011, [Get Paper (PDF)].

Abstract: This paper presents a novel technique for detecting vegetation of virtually all forms in terrestrial laser scanning data of urban environments. We make use of a modern laser range finder capability to measure multiple echoes per laser pulse via Full Wave Analysis. The algorithm is able to efficiently, i.e., less than acquisition time, identify vegetation to a high degree of accuracy (more than 99 percent). We present and evaluate three alternatives to classify candidate regions as either vegetation or non-vegetation.

Jan Elseberg, Dorit Borrmann, and Andreas Nüchter. Efficient Processing of Large 3D Point Clouds. In Proceedings of the XXIII International Symposium on Information, Communication and Automation Technologies (ICAT '11), IEEE Xplore, ISBN 978-1-4577-0746-9, Sarajevo, Bosnia, October 2011, [Get Paper (PDF)].

Abstract: Autonomous robots equipped with laser scanners acquire data at an increasingly high rate. Registration, data abstraction and visualization of this data requires the processing of a massive amount of 3D data. The increasing sampling rates make it easy to acquire Billions of spatial data points. This paper presents algorithms and data structures for handling this data. We propose an efficient octree to store and compress 3D data without loss of precision. We demonstrate its usage for fast 3D scan matching and shape detection algorithms. We evaluate our approach using typical data acquired by mobile scanning platforms.

Andreas Nüchter, Seyedshams Feyzabadi, Deyuan Qiu, and Stefan May. SLAM à la carte - GPGPU for Globally Consistent Scan Matching. In Proceedings of the 4th European Conference on Mobile Robots (ECMR '11), Örebro, Sweden, September 2011 [Get Paper (PDF)].

Abstract: The computational complexity of SLAM is large and constitutes a challenge for real-time processing of a huge amount of sensor data with the limited resources of a mobile robot. Often, notebooks are used to control a mobile system and even these computing devices have nowadays graphics cards which allow general purpose computation using many cores. SLAM à la carte (graphique) exploits these capabilities and carries out 3D scan registrations on the GPU. A speed-up of more than one order of magnitude for precise 3D mapping is reported.

Andreas Nüchter, Stanislav Gutev, Dorit Borrmann, and Jan Elseberg. Skyline-based Registration of 3D Laser Scans. Proceedings of the Joint ISPRS workshop on 3D city modelling & applications and the 6th 3D GeoInfo (3DCMA '11), The Chinese Academic Journal (CD ROM version) CN 11-9251/G or ISSN 1671-6787, Wuhan, China, 2011, [Get Paper].

Abstract: Acquisition and registration of terrestrial 3D laser scans is a fundamental task in mapping and modeling of cities in three dimensions. To automate this task marker-free registration methods are required. Based on the existence of skyline features this paper proposes a novel method. The skyline features are extracted from panoramic 3D scans and encoded as strings enabling the use of string matching for merging the scans. Initial results of the proposed method in the old city center of Bremen are presented.

Jan Elseberg, Dorit Borrmann, and Andreas Nüchter. Eine effiziente Octree-Datenstruktur für das Verarbeiten von großen 3D-Punktwolken. in Photogrammetrie Laserscanning Optische 3D-Messtechnik, Beiträge der Oldenburger 3D-Tage 2011, Fachhochschule Oldenburg/Ostfr./Whv., ISBN 978-3-87907-506-5, pages 72-79, Wichmann Verlag, February 2011.

Zusammenfassung: Dieser Beitrag stellt eine neue Implementation der Octree-Datenstruktur vor, die es ermöglicht, eine Milliarde 3D-Punkte in 8 GB Hauptspeicher exakt zu repräsentieren und effiziente Algorithmen zu implementieren. Der Octree gibt eine Hierarchie vor, die dazu verwendet werden kann, große Punktewolken zu inspizieren und flüssig in ihnen zu navigieren.

Elena Digor, Andreas Birk, and Andreas Nüchter Exploration Strategies for a Robot with a Continously Rotating 3D Scanner, In Proceedings of the Second International Conference on Simulation, Modeling and Programming for Autonomous Robots (SIMPAR '10), Lecture Notes in Computer Science, Volume 6472/2010, ISBN-13 978-3-642-17318-9, pages 374-386, Darmstadt, Germany, November 2010, [Get Paper] [Get Video 1 (MPEG)] [Get Video 1 (MPEG)].

Abstract: To benchmark the efficiency of exploration strategies one has to use robot simulators. In an exploration task, the robot faces an unknown environment. Of course one could test the algorithm in different real-world scenarios, but a competitive strategy must have good performance in any environment that can be systematically constructed inside a simulator. This paper presents an evaluation of exploration strategies we developed for a specific sensor. A continously rotating 3D laser scanner that scans only into one direction at a time moves through the environment sampling the surrounding. Our evaluation framework features an efficient scanning and robot simulator for kinematic feasible trajectories. We will show that shorter trajectories do not necessarily imply quicker exploration. A simple simulator framework is sufficient for evaluating these properties of path planning algorithms.

Jan Elseberg, Dorit Borrmann, Andreas Nüchter, and Kai Lingemann. Non-Rigid Registration and Rectification of 3D Laser Scans, In Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS '10), ISBN 978-1-4244-6676-4, pages 1546-1552, Taipei, Taiwan, October 2010, [Get Paper].

Abstract: Three dimensional point clouds acquired by range scanners often do not represent the environment precisely due to noise and errors in the acquisition process. These latter systematical errors manifest as deformations of different kinds in the 3D range image. This paper presents a novel approach to correct deformations by an analysis of the structures present in the environment and correcting them by non-rigid transformations. The resulting algorithms are used for creating high-accuracy 3D indoor maps.

Kaustubh Pathak, Dorit Borrmann, Jan Elseberg, Narunas Vaskevicius, Andreas Birk, Andreas Nüchter. Evaluation of the Robustness of Planar-Patches based 3D-Registration using Marker-based Ground-Truth in an Outdoor Urban Scenario, In Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS '10), ISBN 978-1-4244-6676-4, pages 5725-5730, Taipei, Taiwan, October 2010, [Get Paper].

Abstract: The recently introduced Minimum Uncertainty Maximum Consensus (MUMC) algorithm for 3D scene registration using planar-patches is tested in a large outdoor urban setting without any prior motion estimate whatsoever. With the aid of a new overlap metric based on unmatched patches, the algorithm is shown to work successfully in most cases. The absolute accuracy of its computed result is corroborated for the first time by ground-truth obtained using reflective markers. There were a couple of unsuccessful scan-pairs. These are analyzed for the reason of failure by formulating two kinds of overlap metrics: one based on the actual overlapping surfacearea and another based on the extent of agreement of rangeimage pixels.We conclude that neither metric in isolation is able to predict all failures, but that both taken together are able to predict the difficulty level of a scan-pair vis-a-vis registration by MUMC.

Dorit Borrmann, Jan Elseberg, Shaan S. Rauniyar, and Andreas Nüchter. Lifelong 3D Mapping – Monitoring with a 3D Scanner, In Proceedings of the IEEE/RSJ IROS Workshop on Robotics for Environmental Monitoring, Taipei, Taiwan, October 2010. [Get Paper]. [Note: This workshop was canceled, but the organizers decided to publish all reviewed and accepted papers online. Please use this link to visit the workshop webpage.

Abstract: Geodesy and surveying are the sciences for monitoring the earth. In recent years traditional surveying equipment has been pushed aside by the emerging technology of laser scanners, that automate the precise measurement of points in the environment. A further step of automation is achieved by operating the surveying equipment automatically and the usage of robotic mapping. Thus, robotic mapping will become a key component in monitoring and surveillance tasks. This paper evaluates a 3D laser scanner from surveying for its usage in robotic monitoring tasks. We examine how seasonal changes and weather conditions impact the data of the 3D scanner and how to deal with these changes. For this analysis 3D scans of various predetermined locations on the campus of the Jacobs University Bremen were taken on a weekly basis over a period of 13 weeks using the RIEGL VZ-400 3D laser range finder. The scans have been registered by means of conventional surveying markers, SIFT features and using our point cloud based 6D SLAM framework. An analysis of the changes in the environment over the course of the scanning period and an evaluation of the matching results complete the analysis.

Dorit Borrmann, Jan Elseberg, Kai Lingemann, and Andreas Nüchter. A Data Structure for the 3D Hough Transform for Plane Detection, in Proceedings of the 5th IFAC Symposium on Intelligent Autonomous Vehicles (IAV '10), Lecce, Italy, September 2010, [Get Paper].

Abstract: The Hough Transform is a well-known method for detecting parametrized objects. It is the de facto standard for the detection of lines and circles in 2-dimensional data sets. For 3D it has attained little attention so far. Apart from computational costs, the main problem is the representation of the accumulator: Usual implementations favor geometrical objects with certain parameters due to uneven sampling of the parameter space. In this paper we present a novel approach to design the accumulator focusing on achieving the same size for each cell. The proposed accumulator is compared to previously known designs.

Jan Wülfing, Joachim Hertzberg, Kai Lingemann, Andreas Nüchter, Thomas Wiemann, and Stefan Stiene. Towards Real Time Robot 6D Localization in a Polygonal Indoor Map Based on 3D ToF Camera Data, in Proceedings of the 5th IFAC Symposium on Intelligent Autonomous Vehicles (IAV '10), Lecce, Italy, September 2010, [Get Paper].

Abstract: This paper reports a method and results for solving the following problem: Given a 3D polygonal indoor map and a mobile robot equipped with a 3D time of flight (ToF) camera, localize at frame rate the 6D robot pose with respect to the map. To solve the problem, the polygonal map is represented for efficient usage as a solid-leaf BSP tree; at each control cycle, the 6D pose change is estimated a priori from odometry or IMU, the expected ToF camera view at the prior pose sampled from the BSP tree, and the pose change estimation corrected a posteriori by fast ICP matching of the expected and the measured ToF image. Our experiments indicate that, first, the method is in fact real-time capable; second, the 6D pose is tracked reliably in a correct map under regular sensor conditions; and third, the tracking can recover from some faults induced by local map inaccuracies and transient or local sensing errors.

Thomas Wiemann, Andreas Nüchter, Kai Lingemann, Stefan Stiene and Joachim Hertzberg. Automatic Construction of Polygonal Maps From Point Cloud Data, in Proceedings of the International Workshop on Safty, Security and Rescue Robotics (SSRR '10), Bremen, Germany, July 2010, [Get Paper].

Abstract: This paper presents a novel approach to create polygonal maps from 3D point cloud data. The gained map is augmented with a interpretation of the scene. Our procedure shows to be fast and reliable and produces accurate maps in indoor environments. The created maps are used with different kinds of sensors for reliable self localization.

Andreas Nüchter, Jan Elseberg, Peter Schneider, and Dietrich Paulus. Linearization of Rotations for Globally Consistent n-Scan Matching, in Proceedings of the IEEE International Conference Robotics and Automation (ICRA '10), ISBN 978-1-4244-5040-4, pages 1373-1379, Anchorage, Alaska, May 2010, [Get Paper (PDF)].

Abstract: The ICP (Iterative Closest Point) algorithm is the de facto standard for geometric alignment of three-dimensional models when an initial relative pose estimate is available. The basis of the algorithm is the minimization of an error function that takes point correspondences into account. While four closed-form solution methods are known for minimizing this function, linearization seems necessary for solving the global scan registration problem. This paper presents such linear solutions for registering n-scans in a global and simultaneous fashion. It studies parameterizations for the rigid body transformations of the n-scan registration problem.

Dorit Borrmann, Jan Elseberg, Kai Lingemann, and Andreas Nüchter. Verbesserte Kartenqualität durch Thin Plate Splines und Hough-Transformation. in Photogrammetrie Laserscanning Optische 3D-Messtechnik, Beiträge der Oldenburger 3D-Tage 2010, Fachhochschule Oldenburg/Ostfr./Whv., ISBN 978-3-87907-494-5, pages 134-141, Wichmann Verlag, February 2010.

Abstract: Laserscanner sind präzise Messgeräte zur Ermittlung von Distanzwerten. Dennoch weist eine jede mit einem Laserscanner akquirierte Punktwolke Fehler auf, die auch durch Kalibrierung nicht vollständig verhindert werden können. Neben Sensorrauschen kommt es auch zu systematischen Fehlern. Die meisten künstlich geschaffenen Umgebungen bestehen aus einer großen Anzahl ebener Flächen, die helfen können, die Qualität von Laserscan-Karten zu verbessern. Dieser Aufsatz stellt Methoden vor, die unter Zuhilfenahme von ebenen Umgebungsstrukturen die Fehler in den Laserscans durch nicht-rigide Verformungen verringern.

Andreas Nüchter. 6D SLAM mit Global Konsistentem Scanmatching, In Terrestrisches Laserscanning (TLS 2009) Beiträge zum 91. DVW-Seminar am 18. und 19. November in Fulda, (invited paper), ISBN 978-3-89639-734-8, pages 69-92, Fulda, Germany, November 2009.

Einleitung: Terrestrisches Laserscanning (TLS) hat die in den letzten Jahren die Vermessungstechnik revolutioniert. Durch die Entwicklung des kinematischen terrestrischen Laserscannings (k-TLS) oder Mobile Mapping, das die Aufnahme von geometrische Umgebungsinformation von einer bewegten Plattform aus erlaubt, wurde ein wesentlicher Schritt zur weiteren Automatisierung in der Vermessungstechnik getan. Leider ist k-TLS nicht überall einsetzbar, da neben den Daten des Laserscanners hochgenaue Informationen über die Pose (Position und Orientierung) der mobilen Plattform vorliegen müssen.
Technischer Fortschritt erlaubt den Bau von autonomen Robotersystemen, die mit 3D-Laserscannern ausgestattet sind und es besteht Potential für weitere Automatisierung. Dazu muss das Problem der gleichzeitigen Lokalisation und Kartierung gelöst werden. Dieses klassische Robotikproblem ist ein Henne-und-Ei-Problem: Mit genauster Kenntnis der Position des mobilen Roboters lassen sich korrekte Karten erzeugen. Mit Hilfe von Karten können sich Roboter sehr genau lokalisieren. Beides gleichzeitig durchzuführen stellt neue hohe Anforderungen an die Algorithmen, die Scannerdaten verarbeiten.
...

Deyuan Qiu, Stefan May, and Andreas Nüchter. GPU-accelerated Nearest Neighbor Search for 3D Registration. In Proceedings of the 7th International Conference on Computer Vision Systems (ICVS '09). LNCS 5815, Spinger ISBN 978-3-642-04666-7, pages 194-203, Lìege Belgium, October 2009. [Get Paper (PDF)]

Nearest Neighbor Search (NNS) is employed by many computer vision algorithms. The computational complexity is large and constitutes a challenge for real-time capability. The basic problem is in rapidly processing a huge amount of data, which is often addressed by means of highly sophisticated search methods and parallelism. We show that NNS based vision algorithms like the Iterative Closest Points algorithm (ICP) can achieve real-time capability while preserving compact size and moderate energy consumption as it is needed in robotics and many other domains. The approach exploits the concept of general purpose computation on graphics processing units (GPGPU) and is compared to parallel processing on CPU. We apply this approach to the 3D scan registration problem, for which a speed-up factor of 88 compared to a sequential CPU implementation is reported.

Jochen Sprickerhof, Andreas Nüchter, Kai Lingemann, Joachim Hertzberg. An Explicit Loop Closing Technique for 6D SLAM, In Proceedings of the 4th European Conference on Mobile Robots (ECMR '09), Mlini/Dubrovnic, Croatia, September 2009. [ Get Paper (PDF)] [Get Videos].

Abstract: Simultaneous Localization and Mapping (SLAM) is the problem of building a map of an unknown environment by a mobile robot while at the same time navigating the environment, using the unfinished map. For SLAM, two tasks have to be solved: First reliable feature extraction and data association, second the optimal estimation of poses and features. These two parts are often referred to as SLAM frontend and backend. Algorithms that solve SLAM by using laser scans commonly rely on matching closest points in the frontend part. Then the SLAM front- and backend have to be iterated to ensure that the map converges.
This paper presents a novel approach for solving SLAM using 3D laser range scans. We aim at avoiding the iteration between the SLAM front- and backend and propose a novel explicit loop closing heuristic (ELCH). It dissociates the last scan of a sequence of acquired scans, reassociates it to the map, built so far by scan registration, and distributes the difference in the pose error over the SLAM graph. We describe ELCH in the context of SLAM with 3D scans considering 6 DoF. The performance is evaluated using ground truth data of an urban environment.

Stefan May, David Dröschel, Dirk Holz, Stefan Fuchs, Andreas Nüchter. Robust 3D-Mapping with Time-of-Flight Cameras, In Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS '09), ISBN 978-1-4244-3804-4, St. Louis, MO, USA, October 2009.

Abstract: Time-of-Flight cameras constitute a smart and fast technology for 3D robotic perception but lack in measurement precision and robustness. We present a comprehensive approach for 3D environment mapping based on this technology. Imprecision of depth measurements are properly handled by calibration and application of several filters. Robust registration is performed by a novel extension to the Iterative Closest Point algorithm. Remaining registration errors are refined by global relaxation after loop-closure and surface smoothing. A laboratory ground truth evaluation is provided as well as 3D mapping experiments in a larger indoor environment.

Martin Magnusson, Henrik Andreasson, Andreas Nüchter, Achim J. Lilienthal. Appearance-Based Place Recognition from 3D Laser Data Using the Normal Distributions Transform, in Proceedings of the IEEE International Conference Robotics and Automation (ICRA '09), ISBN 987-1-4244-2789-5, pages 23 - 28, Kobe, Japan, May 2009 [Get Paper (PDF)].

Abstract: To advance robotic science it is important to perform experiments that can be replicated by other researchers to compare different methods. However, these comparisons tend to be biased, since re-implementations of reference methods often lack thoroughness and do not include the hands-on experiences obtained during the original development process. This paper presents the results of a field experiment, carried out by two research groups that are leading in the field of 3D robotic mapping. The iterative closest points algorithm (ICP) is compared to the normal distributions transform (NDT).
We also present an improved version of NDT with a substantially larger valley of convergence than previously published versions.

Martin Magnusson, Andreas Nüchter, Christopher Lörken, Achim, J. Lilienthal, and Joachim Hertzberg. Evaluation of 3D Registration Reliability and Speed – A Comparison of ICP and NDT in Proceedings of the IEEE International Conference Robotics and Automation (ICRA '09), ISBN 987-1-4244-2789-5, pages 3907 - 3912, Kobe, Japan, May 2009 [Get Paper (PDF)].

Abstract: We propose a new approach to appearance based place recognition from metric 3D maps, exploiting the NDT surface representation. Locations are described with feature histograms based on surface orientation and smoothness, and loop closure can be detected by matching feature histograms.
We also present a quantitative performance evaluation using two real-world data sets, one of which is highly self-similar, showing that the proposed method works well in different environments.

Andreas Nüchter and Jan Elseberg. Linearisierte Lösung der ICP-Fehlerfunktion für global konsistentes Scanmatching. in Photogrammetrie Laserscanning Optische 3D-Messtechnik, Beiträge der Oldenburger 3D-Tage 2009, Fachhochschule Oldenburg/Ostfr./Whv., ISBN 978-3-87907-478-5, Wichmann Verlag, pages 74 - 81, 2009.

Zusammenfassung: Dieser Artikel beschreibt eine Linearisierung in geschlossener Form für die Minimierung der Fehlerfunktion, die beim ICP-Algorithmus auftaucht. Die Linearisierung approximiert die tatsächliche Lösung und nutzt die Annahme aus, dass die auftretenden Winkel klein sind. Weiterhin zeigt der Artikel die Möglichkeit auf, die Linearisierung für global konsistentes Scanmatching zu verwenden. Global konsistentes Scanmatching minimiert den Gesamtfehler, wenn mehr als zwei 3D-Punktwolken vorliegen.

Andreas Nüchter, Kai Lingemann, and Joachim Hertzberg. Evaluating a 3D Camera for RoboCup Rescue. In Proceedings of the SICE Annual Conference 2008: International Conference on Instrumentation, Control and Information Technology (SICE '08), ISBN 978-4-907764-29-6, pp. 2070-2075, Tokyo, Japan, August, 2008.

Abstract: The following paper evaluates a time-of-flight 3D camera with regards to its usability for RoboCup Rescue. This includes an evaluation of the influence of outer conditions to the camera data, as well as its usage for automatic 3D mapping by scan registration. A color camera is calibrated with respect to the 3D camera in order to gain colored texture information for the acquired measurements.

Dorit Borrmann, Jan Elseberg, Kai Lingemann, Andreas Nüchter, and Joachim Hertzberg. The Efficient Extension of Globally Consistent Scan Matching to 6 DoF. In Proceedings of the 4th International Symposium on 3D Data Processing, Visualization and Transmission (3DPVT '08), Available electronically as Tech Report GT-IC-08-05 from the Georgia Institute of Technology, Atlanta, GA, USA, pages 29-36, June 2008 [Get Paper] [Get Video] [Addendum].

Abstract: Over ten years ago, Lu and Milios presented a probabilistic scan matching algorithm for solving the simultaneous localization and mapping (SLAM) problem with 2D laser range scans, a standard in robotics. This paper presents an extension to this GraphSLAM method. Our iterative algorithm uses a sparse network to represent the relations between several overlapping 3D scans, computes in every step the 6 degrees of freedom (DoF) transformation in closed form and exploits efficient data association with cached k-d trees. Our approach leads to globally consistent 3D maps, precise 6D pose and covariance estimates, as demonstrated by various experimental results.

Andreas Nüchter, Kai Lingemann, Dorit Bormann, Jan Elseberg, and Jan Böhm. Global Konsistente 3D-Kartierung mit Scanmatching. in Photogrammetrie Laserscanning Optische 3D-Messtechnik, Beiträge der Oldenburger 3D-Tage 2008, Fachhochschule Oldenburg/Ostfr./Whv. ISBN 978-3-87907-463-1, Wichmann Verlag, pages 194 - 201, February 2008.

Abstract: Das Einpassen bzw. Registrieren von Punktmengen unter starren Transformationen ist eines der Grundprobleme in der Bildverarbeitung. Hierbei können die 3D-Daten aus Laserscannern, Stereokameras u.ä. stammen. Für zwei 3D-Punktmengen bildet der ICP-Algorithmus (Iterative Closest Points) einen de facto Standard für das Registrieren. Weitet man diesen Algorithmus jedoch auf viele 3D-Scans aus, akkumulieren sich Registrierungsfehler. Der vorliegende Beitrag skizziert einen neuen Algorithmus für das global konsistente 3D-Scanmatching (Borrmann, Elseberg, Lingemann, Nüchter und Hertzberg 2008) und zeigt eine Anwendung für das Erfassen von Gebäuden. Die Genauigkeit des Algorithmus wird bezüglich geodätischer Methoden evaluiert.

Oliver Wulf, Andreas Nüchter, Joachim Hertzberg, and Bernardo Wagner. Ground Truth Evaluation of Large Urban 6D SLAM. In Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS '07), pages 650 - 657, ISBN 1-4244-0912-8, San Diego, CA, USA, October - November, 2007 [Get Paper]. [Get Videos]

Abstract: In the past many solutions for simultaneous localization and mapping (SLAM) have been presented. Recently these solutions have been extended to map large environments with six degrees of freedom (DoF) poses. To demonstrate the capabilities of these SLAM algorithms it is common practice to present the generated maps and successful loop closing. Unfortunately there is often no objective performance metric that allows to compare different approaches. This fact is attributed to the lack of ground truth data. For this reason we present a novel method that is able to generate this ground truth data based on reference maps. Further on, the resulting reference path is used to measure the absolute performance of different 6D SLAM algorithms building a large urban outdoor map.

Andreas Nüchter. Parallelization of Scan Matching for Robotic 3D Mapping. In Proceedings of the 3rd European Conference on Mobile Robots (ECMR '07), Freiburg, Germany, September 2007, [Get Paper], [View Online Proceedings].

Abstract: Robotic 3D Mapping of environments is computationally expensive, since 3D scanners sample the environment with many data points. In addition, the solution space grows exponentially with the additional degrees of freedom needed to represent the robot pose. Mapping environments in 3D must regard six degrees of freedom to characterize the robot pose. This paper extends our solution to the 3D mapping problem by parallelization. The availability of multi-core processors as well as efficient programming schemes as OpenMP permit the parallel execution of robotics task with on-board means.

Andreas Bartel, Frank Meyer, Christopher Sinke, Thomas Wiemann, Andreas Nüchter, Kai Lingemann, and Joachim Hertzberg. Real-Time Outdoor Trail Detection on a Mobile Robot. In Proceedings of the 13th IASTED International Conference on Robotics and Applications, ISBN 978-0-88986-686-7, pages 477 - 482, Würzburg, Germany, August 2007, [Get Paper and Videos].

Abstract: In this paper we present a reliable approach for real-time outdoor trail following and obstacle avoidance. The trail classification is done using an off-the-shelf webcam and a pitched 2D laser scanner on a KURT2 robot equipped with an Intel Centrino laptop. This simple setup enables us to follow given pathways of different kinds using a GPS receiver for rough orientation.

Andreas Nüchter, Kai Lingemann, and Joachim Hertzberg. 6D SLAM with Cached k-d tree Search. In Proceedings of the 13th IASTED International Conference on Robotics and Applications, ISBN 978-0-88986-686-7, pages 181 - 186, Würzburg, Germany, August 2007.

Abstract: 6D SLAM (Simultaneous Localization and Mapping) or 6D Concurrent Localization and Mapping of mobile robots considers six degrees of freedom for the robot pose, namely, the x, y and z coordinates and the roll, yaw and pitch angles. In previous work we presented our scan matching based 6D SLAM approach [cite deleted], where scan matching is based on the well known iter ative closest point (ICP) algorithm [3]. Effcient implementations of this algorithm are a result of a fast computation of closest points. The usual approach, i.e., using k-d trees is extended in this paper. We describe a novel search strategy, that lead s to significant speed-ups. Our mapping system is real-time capable, i.e., 3D maps are computed using the resources of the used robotic hardware.

Rolf Lakaemper, Andreas Nüchter, Nagesh Adluru, and Longin Jan Latecki. Performance of 6D LuM and FFS SLAM - An Example for Comparison using Grid and Pose Based Evaluation Methods. In Proceedings of seventh workshop on Performance Metrics for Intelligent Systems (PerMIS '07), Washington D.C., USA, August 2007, [Get Paper (PDF)].

Abstract: The focus of this paper is on the performance comparison of two simultaneous localization and mapping (SLAM) algorithms namely 6D Lu/Milios SLAM and Force Field Simulation (FFS). The two algorithms are applied to a 2D data set. Although the algorithms generate overall visually comparable results, they show strengths and weaknesses in different regions of the generated global maps. The question we address in this paper is, if different ways of evaluating the performance of SLAM algorithms project different strengths and how can the evaluations be useful in selecting an algorithm. We will compare the performance of the algorithms in different ways, using grid and pose based quality measures.

Andreas Nüchter, Kai Lingemann, and Joachim Hertzberg. Cached k-d tree search for ICP algorithms. In Proceedings of the 6th IEEE International Conference on Recent Advances in 3D Digital Imaging and Modeling (3DIM '07), IEEE Computer Society Press, ISBN 0-7695-2939-9, pages 419 - 426, Montreal, Canada, August 2007, [Get Paper (PDF)] [HTML Version].

Abstract: The ICP (Iterative Closest Point) algorithm is the de facto standard for geometric alignment of three-dimensional models when an initial relative pose estimate is available. The basis of ICP is the search for closest points. Since the development of ICP, k-d trees have been used to accelerate the search. This paper presents a novel search procedure, namely cached k-d trees, exploiting iterative behavior of the ICP algorithm. It results in a significant speed-up of about 50% as we show in an evaluation using different data sets.

Giovanni Indiveri, Andreas Nüchter, and Kai Lingemann. High Speed Differential Drive Mobile Robot Path Following Control With Bounded Wheel Speed Commands, in Proceedings of the IEEE International Conference Robotics and Automation (ICRA '07), ISBN 1-4244-0602-1, pages 2202 - 2207, Rome, Italy, April 2007, [Get Paper (PDF)].

Abstract: The great majority of path following control laws for either kinematical or dynamical mobile robot models are designe d assuming ideal actuators, i.e. assuming that any commanded velocity or torque (in the kinematical and dynamical ca ses respectively) will be instantly implemented regardless of its value. Real actuators are far from being ideal. In particular, only bounded velocities and torques can be realized for any given command. With reference to the kinemati cal model of a differential drive mobile robot, a known path following control law is modified to account for actuator velocity saturation. The proposed solution is experimentally shown to be particularly useful for high speed applica tions where accounting for actuator velocity saturation may have a large influence on performance.

Lars Kunze, Kai Lingemann, Andreas Nüchter, and Joachim Hertzberg. Salient Visual Features to Help Close the Loop in 6D SLAM, in Proceedings of the ICVS Workshop on Computational Attention & Applications (WCAA '07), Bielefeld, Germany, ISBN 978-3-00-020933-8, March 2007, [Get Paper (PDF)].

Abstract: One fundamental problem in mobile robotics research is Simultaneous Localization and Mapping (SLAM): A mobile robot has to localize itself in an unknown environment, and at the same time generate a map of the surrounding area. One fundamental part of SLAM algorithms is loop closing: The robot detects whether it has reached an area that has been visited before, and uses this information to improve the pose estimate in the next step. In this work, visual camera features are used to assist closing the loop in an existing 6 degree of freedom SLAM (6D SLAM) architecture. For our robotics application we propose and evaluate several detection methods, including salient region detection and maximally stable extremal region detection. The detected regions are encoded using SIFT descriptors and stored in a database. Loops are detected by matching of the images' descriptors. A comparison of the different feature detection methods shows that the combination of salient and maximally stable extremal regions suggested by performs moderately.

Andreas Nüchter. Algorithmen zur Erstellung virtueller 3D-Welten mit mobilen Robotern, in Photogrammetrie Laserscanning Optische 3D-Messtechnik, Beiträge der Oldenburger 3D-Tage 2007, Fachhochschule Oldenburg/Ostfr./Whv, ISBN 978-3-87907-447-1, Wichmann Verlag, pages 164 - 171, February 2007.

Zusammenfassung: 3D-Laserscanner sind eine junge Technologie, die die Erfassung räumlicher Daten revolutioniert und Robotern das dreid imensionale Abtasten von Objekten möglich macht. Roboter, die ihre Umgebung dreidimensional kartieren können, eignen sich zum automatischen Erstellen virtuelle 3D-Welten. Eine 3D-Welt, oder 3D-Umgebungskarte muss mit der wirklichen Umgebung übereinstimmen, also korrekt und konsistent sein. Ist die Position des Roboters genau bekannt, können die loka len Karten auf der Grundlage dieser Position zusammengefügt werden. Leider ist die Selbstlokalisation eines Roboters stets fehlerbehaftet. Daher darf der Kartenbau nicht nur auf der Roboterposition basieren, sondern muss auch auf der Grundlage der Sensorwerte geschehen. In diesem Zusammenhang spricht man vom simultanen Lokalisations- und Kartierungs problem (SLAM, simultaneous localization and mapping problem). Korrekte, global konsistente Modelle entstehen durch e inen 6D-SLAM Algorithmus. Hierbei werden 6 Freiheitsgrade in der Roboterpose berücksichtigt, geschlossene Kreise erka nnt und der globale Fehler minimiert. Die Basis des 6D-SLAM ist ein sehr schneller ICP-Algorithmus.

Andreas Nüchter, Kai Lingemann and Joachim Hertzberg. 6D SLAM with Kurt3D, in Robotic 3D Environment Cognition, Workshop at the International Conference Spatial Cognition, Bremen, Germany 2006. [Get Paper (PDF)]

Abstract: 6D SLAM (Simultaneous Localization and Mapping) or 6D Concurrent Localization and Mapping of mobile robots considers six dimensions for the robot pose, namely, the x, y and z coordinates and the roll, yaw and pitch angles. Robot motion and localization on natural surfaces, e.g., when driving with a mobile robot outdoor, must regard these degrees of freedom. 3D (6 DOF) scan matching, combined with a heuristic for closed loop detection and a global relaxation method, results in a highly precise mapping system for outdoor environments. The mobile robot Kurt3D is capable to run the mapping process with its on-board sensors and computers and is used to digitalize different environments. This paper summarizes our previous research.

Andreas Nüchter, Kai Lingemann, Joachim Hertzberg, and Hartmut Surmann. 6D SLAM – Mapping Outdoor Environments, in Proceedings of the International Workshop on Safty, Security and Rescue Robotics (SSRR '06), (CDROM Proceedings), Gaithersburg, Maryland, USA, August 2006,

Abstract: 6D SLAM (Simultaneous Localization and Mapping) of mobile robots considers six dimensions for the robot pose, namely, the x, y and z coordinates and the roll, yaw and pitch angles. Robot motion and localization on natural surfaces, e.g., when driving with a mobile robot outdoor, must regard these degrees of freedom. This paper presents a robotic mapping method based on locally consistent 3D laser range scans. Scan matching, combined with a heuristic for closed loop detection and a global relaxation method, results in a highly precise mapping system for outdoor environments. The mobile robot Kurt3D was used to acquire data of the Schloss Birlinghoven campus. The resulting 3D map is compared with ground truth, given by an aerial photograph.

Sven Albrecht, Joachim Hertzberg, Kai Lingemann, Andreas Nüchter, Jochen Sprickerhof, Stefan Stiene. Device Level Simulation of Kurt3D Rescue Robots, in Third International Workshop on Synthetic Simulation and Robotics to Mitigate Earthquake Disaster (SRMED 2006). CDROM Proceedings, June 2006 [Get Paper (PDF)] [Get Paper (HTML)].

Abstract: USARSIM is a worldwide used robot simulator deployed in Urban Search and Rescue (USAR) and in the context of the RoboCup Rescue Real Robot contest. This paper describes the USARSIM simulator for KURT2 and Kurt3D robot platforms, which we are using in both education and research. As it simulates on the device level, a seamless integration of real robot control software with the simulations becomes possible. We evaluate the performance for simulating laser range scans and the camera system. In addition, we show a simulation of the rescue robots.

Stefan Stiene, Kai Lingemann, Andreas Nüchter, and Joachim Hertzberg. Contour-based Object Detection in Range Images, in Proceedings of the Third International Symposium on 3D Data Processing, Visualization and Transmission (3DPVT '06), CDROM Proceedings, June 2006. [Get Paper (PDF)]

Abstract: This paper presents a novel object recognition approach based on range images. Due to its insensitivity to illumination, range data is well suited for reliable silhouette extraction. Silhouette or contour descriptions are good sources of information for object recognition. We propose a complete object recognition system, based on a 3D laser scanner, reliable contour extraction with floor interpretation, feature extraction using a new, fast Eigen-CSS method, and a supervised learning algorithm. The recognition system was successfully tested on range images acquired with a mobile robot, and the results are compared to standard techniques, i.e., Geometric features, Hu and Zernike moments, the Border Signature method and the Angular Radial Transformation. An evaluation using the receiver operating characteristic analysis completes this paper. The Eigen-CSS method has proved to be comparable in detection performance to the top competitors, yet faster than the best one by an order of magnitude in feature extraction time.

Andreas Nüchter, Kai Lingemann, and Joachim Hertzberg. Extracting Drivable Surfaces in Outdoor 6D SLAM, in Proceedings of the 37nd International Symposium on Robotics (ISR '06) and 4th German Conference Robotik 2006, ISBN 3-18-091956-6, Munich, Germany, 2006. [Get Paper (PDF)] [Get Paper (HTML)] [Get Surface Animation (DivX)] [Get Marching Cubes Representation (DivX)]

Abstract: A basic issue of mobile robotics is generating environment maps automatically. Outdoor terrain is challenging since the ground is uneven and the surrounding is structured irregularly. In earlier work, we have introduced 6D SLAM (Simultaneous Localization and Mapping) as a method to taking all six DOF of robot poses (x, y, z translation; roll, pitch, yaw angles) into account. This paper adds to 6D SLAM a method for extracting drivable surfaces in the 3D maps while they are being generated. Experiments have been made in a Botanical Garden, with drivable surfaces consisting of gravel paths or lawn, both involving significant slope.

Kai Lingemann, Andreas Nüchter, Joachim Hertzberg, and Hartmut Surmann. About the Control of High Speed Mobile Indoor Robots, in Proceedings of the Second European Conference on Mobile Robotics (ECMR '05), ISBN 88-89177-187, Ancona, Italy, September 2005, pages 218 - 223. [Get Paper and Video]

Abstract: This paper describes the control algorithms of the high speed mobile robot Kurt3D. Kurt3D drives up to 4 m/s autonomously and reliably in an unknown office environment. We present the reliable hardware, fast control cycle algorithms and a novel set value computation scheme for achieving these velocities. In addition we sketch a real-time capable laser based position tracking method that is well suited for driving with these velocities.

Joachim Hertzberg, Kai Lingemann, and Andreas Nüchter. USARSIM – Game-Engines in der Robotik-Lehre, in A. B. Cremers et al. (eds.): Informatik 2005 – Informatik LIVE, vol.1 (Beiträge der 35. Jahrestagung der Gesellschaft für Informatik, Bonn). ISBN 3-88579-396-2, pages 158-162 Gesellschaft für Informatik, Bonn, Germany, September 2005. [Get Paper (PDF)].

Abstract: In der Lehre zum Thema Wissensbasierte Robotik verwenden wir seit Kurzem den Robotersimulator USARSIM, der weltweit im Kontext der RoboCup Rescue Real Robot Liga eingesetzt wird. Wir stellen den Lehr-Kontext vor, in dem wir arbeiten, skizzieren den Simulator und beschreiben seine Einbindung in unsere Lehre. Unsere Erfahrungen bezuglich der Motivation der Studierenden und ihrer Leistungen der Verwendung des Simulators sind sehr positiv.

Andreas Nüchter, Kai Lingemann, Joachim Hertzberg, and Hartmut Surmann. Heuristic-Based Laser Scan Matching for Outdoor 6D SLAM, in KI 2005: Advances in Artificial Intelligence. 28th Annual German Conference on AI, Proceedings. Springer (Berlin) LNAI vol. 3698, ISBN 3-540-28761-2, pages 304-319. Koblenz, Germany, September 2005. [Get Paper and Video]

Abstract: 6D SLAM (Simultaneous Localization and Mapping) or 6D Concurrent Localization and Mapping of mobile robots considers six dimensions for the robot pose, namely, the x, y and z coordinates and the roll, yaw and pitch angles. Robot motion and localization on natural surfaces, e.g., driving with a mobile robot outdoor, must regard these degrees of freedom. This paper presents a robotic mapping method based on locally consistent 3D laser range scans. Scan matching, combined with a heuristic for closed loop detection and a global relaxation method, results in a highly precise mapping system for outdoor environments. The mobile robot Kurt3D was used to acquire data of the Schloss Birlinghoven campus. The resulting 3D map is compared with ground truth, given by an aerial photograph.

Andreas Nüchter, Kai Lingemann, Joachim Hertzberg, and Hartmut Surmann. Accurate Object Localization in 3D Laser Range Scans, in Proceedings of the 12th International Conference on Advanced Robotics (ICAR '05), ISBN 0-7803-9178-0, pages 665 - 672, Seattle, USA, July 2005, [Get Paper (PDF)] [Get Paper (HTML)].

Abstract: This paper presents a novel method for object detection and classification in 3D laser range data that is acquired by an autonomous mobile robot. Unrestricted objects are learned using classification and regression trees (CARTs) and using an Ada Boost learning procedure. Off-screen rendered depth and reflectance images serve as an input for learning. The performance of the classification is improved by combining both sensor modalities, which are independent from external light. This enables highly accurate, fast and reliable 3D object localization with point matching. Competitive learning is used for evaluating the accuracy of the object localization.

Andreas Nüchter, Kai Lingemann, Joachim Hertzberg, and Hartmut Surmann. 6D SLAM with Approximate Data Association, in Proceedings of the 12th International Conference on Advanced Robotics (ICAR '05), ISBN 0-7803-9178-0, pages 242 - 249, Seattle, USA, July 2005, [Get Paper (PDF)] [Get Paper (HTML)].

Abstract: This paper provides a new solution to the simultaneous localization and mapping (SLAM) problem with six degrees of freedom. A fast variant of the Iterative Closest Points (ICP) algorithm registers 3D scans taken by a mobile robot into a common coordinate system and thus provides relocalization. Hereby, data association is reduced to the problem of searching for closest points. Approximation algorithms for this searching, namely, approximate kd-trees and box decomposition trees, are presented and evaluated in this paper. A solution to 6D SLAM that considers all free parameters in the robot pose is built based on 3D scan matching.

Andreas Nüchter, Oliver Wulf, Kai Lingemann, Joachim Hertzberg, Bernardo Wagner, and Hartmut Surmann, 3D Mapping with Semantic Knowledge, in Proceedings of the RoboCup International Symposium 2005, Osaka, Japan, July 2005, [Get Paper (PDF)] [Get Paper (HTML)].

Abstract: A basic task of rescue robot systems is mapping of the environment. Localizing injured persons, guiding rescue workers and excavation equipment requires a precise 3D map of the environment. This paper presents a new 3D laser range finder and novel scan matching method for the robot Kurt3D [9]. Compared to previous machinery [12], the apex angle is enlarged to 360 . The matching is based on semantic information. Surface attributes are extracted and incorporated in a forest of search trees in order to associate the data, i.e., to establish correspondences. The new approach results in advances in speed and reliability.

Andreas Nüchter, Kai Lingemann, Joachim Hertzberg, Hartmut Surmann, Kai Pervölz, Matthias Hennig, K. R. Tiruchinapalli, Rainer Worst, and Thomas Christaller, Mapping of Rescue Environments with Kurt3D, in Proceedings of the International Workshop on Safty, Security and Rescue Robotics (SSRR '05), ISBN 0-7803-8946-8, pages 158 - 163, Kobe, Japan, June 2005, (best paper award) [Get Paper (PDF)].

Abstract: Deploying rescue workers in an urban setting is often a perilous, time-, power-, and force-consuming job, and systems to assist in this effort are needed. A fundamental task for rescue is to localize injured persons. To this end, robotic systems are used for mapping a site and for remote inspection of suspicious objects. The mobile robot Kurt3D is the first rescue robot that is capable of mapping its environment in 3D and self localize in all six degrees of freedom, i.e., considering its x, y and z positions and the roll, yaw and pitch angles.

Sara Mitri, Simone Frintrop, Kai Pervölz, Hartmut Surmann, and Andreas Nüchter. Robust Object Detection at Regions of Interest with an Application in Ball Recognition, in Proceedings IEEE 2005 International Conference Robotics and Automation (ICRA '05), ISBN 0-7803-8915-8, pages 126 - 131, Barcelona, Spain, April 2005, [Get Paper (PDF)] [Get Paper (HTML)].

Abstract: In this paper, we present a new combination of a biologically inspired attention system (VOCUS Visual Object detection with a Computational attention System) with a robust object detection method. As an application, we built a reliable system for ball recognition in the RoboCup context. Firstly, VOCUS finds regions of interest generating a hypothesis for possible locations of the ball. Secondly, a fast classifier verifies the hypothesis by detecting balls at regions of interest. The combination of both approaches makes the system highly robust and eliminates false detections. Furthermore, the system is quickly adaptable to balls in different scenarios: The complex classifier is universally applicable to balls in every context and the attention system improves the performance by learning scenario-specific features quickly from only a few training examples. Index Terms - visual attention, object classification.

Simone Frintrop, Andreas Nüchter, Hartmut Surmann, and Joachim Hertzberg. Saliency-based Object Recognition in 3D Data, in Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS '04), ISBN 0-7803-8464-4, pages 2167 - 2172, Sendai, Japan, September 2004. [Get Paper (PDF)]

Abstract: This paper presents a robust and real-time capable recognition system for the fast detection and classification of objects in spatial 3D data. Depth and reflection data from a 3D laser scanner are rendered into images and fed into a saliency-based visual attention system that detects regions of potential interest. Only these regions are examinated by a fast classifier. The time saving of classifying objects in salient regions rather than in complete images is linear with the number of trained object classes. Robustness is achieved by the fusion of the bi-modal scanner data; in contrast to camera images, this data is completely illumination independent. The recognition system is trained for two different object classes and evaluated on real indoor data.

Kai Lingemann, Hartmut Surmann, Andreas Nüchter, and Joachim Hertzberg. Indoor and Outdoor Localization for Fast Mobile Robots, in Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS '04), ISBN 0-7803-8464-4, pages 2185 - 2190, Sendai, Japan, September 2004. [Get Paper (PDF)]

Abstract: This paper describes a novel, laser-based approach for tracking the pose of a high-speed mobile robot. The algorithm is outstanding in terms of accuracy and computational time, being 33 times faster than real time. The efficiency is achieved by a closed form solution for the matching of two laser scans, the use of natural landmarks and fast linear filters. The implemented algorithm is evaluated with the high-speed robot Kurt3D (4 m/s), and compared to standard scan matching methods in indoor and outdoor environments.

Sara Mitri, Kai Pervölz, Hartmut Surmann, and Andreas Nüchter. Fast Color-Independent Ball Detection for Mobile Robots, in Proceedings of the IEEE International Conference Mechatronics and Robotics 2004 (MechRob '04), ISBN 3-938153-50-X, pages 900 - 905, Aachen, Germany, September 2004. [Get Paper (PDF)] [Get Paper (HTML)]

Abstract: This paper presents a novel scheme for fast color invariant ball detection in the RoboCup context. Edge filtered camera images serve as an input for an Ada Boost learning procedure that constructs a cascade of classification and regression trees (CARTs). Our system is capable to detect different soccer balls in the RoboCup and other environments. The resulting approach for object classification is real-time capable and reliable.

Sandor Fekete, Rolf Klein, and Andreas Nüchter. Online Searching with an Autononmous Robot, in Algorithmic Foundations of Robotics VI, STAR 17 (Proccedings of the 6th International Workshop on the Algorithmic Foundations of Robotics (WAFR '04)), Springer Tracts in Advanced Robotics, Vol. 17, ISBN 3-540-25728-4, pages 139 - 154, Zeist/Utrecht, The Netherlands, July 2004 (2005), [Get Paper and Video]

Abstract: We discuss online strategies for visibility-based searching for an ob ject hidden behind a corner, using Kurt3D, a real autonomous mobile robot. This task is closely related to a number of well-studied problems. Our robot uses a threedimensional laser scanner in a stop, scan, plan, go fashion for building a virtual three-dimensional environment. Besides planning tra jectories and avoiding obstacles, Kurt3D is capable of identifying objects like a chair. We derive a practically useful and asymptotically optimal strategy that guarantees a competitive ratio of 2, which differs remarkably from the well-studied scenario without the need of stopping for surveying the environment. Our strategy is used by Kurt3D, documented in a separate video.

Andreas Nüchter, Hartmut Surmann, Kai Lingemann, and Joachim Hertzberg. 6D SLAM - Preliminary Report on closing the loop in Six Dimensions, in Proceedings of the 5th IFAC Symposium on Intelligent Autonomous Vehicles (IAV '04), Elsevier, ISBN 008-044237-4, Lissabon, Portugal, June 2004 (2005), [Get Paper and Video].

Abstract: To create 3D volumetric maps of scenes with autonomous mobile robots it is necessary to gage several 3D scans and to merge them into one consistent 3D model. This paper provides a new solution to the simultaneous localization and mapping (SLAM) problem with six degrees of freedom. Robot motion on natural surfaces has to cope with yaw, pitch and roll angles, turning pose estimation into a problem in six mathematical dimensions. A fast variant of the Iterative Closest Points (ICP) algorithm registers the 3D scans in a common coordinate system and relocalizes the robot. Finally, consistent 3D maps are generated using closing loop detection and a global relaxation. Keywords: autonomous mobile robots, 3D laser scanner, 3D scan matching, simultaneous localization and mapping (SLAM), closing loop.

Sandor Fekete, Rolf Klein, and Andreas Nüchter. Searching with an Autononmous Robot, in Proccedings of the 20th ACM Annual Symposium on Computational Geometry (SoCG '04), pages 449 - 450, ACM Press, ISBN 1-58113-885-7, New York, USA, June 2004, [Get Abstract and Video].

Abstract: We demonstrate how one of the classical areas of computational geometry has reached practical application, which in turn gives rise to new, fascinating geometric problems. In particular, we discuss the problem of developing a good online strategy for an autonomous mobile robot to locate an object that is hidden behind a corner or door.

Kai Pervölz, Andreas Nüchter, Hartmut Surmann, and Joachim Hertzberg. Automatic Reconstruction of Colored 3D Models in Proceedings of Robotik 2004, VDI-Berichte 1841, pages 215 - 222, Munich, Germany, ISBN 3-18-091841-1, June 2004, [Get Paper (PDF)] [HTML version].

Abstract: A basic issue of mobile robotics is the automatic generation of environment maps. This paper presents novel results for the reconstruction of textured 3D maps with an autonomous mobile robot, a 3D laser range finder and two pan-tilt color cameras. Building 3D maps involves a number of fundamental scientific issues. This paper adresses the issue of how to fuse the geometry data of the 3D laser range finder with camera images. The proposed algorithm allows to texturize geometrical 3D scenes-models.

Simone Frintrop, Andreas Nüchter and Hartmut Surmann. Visual Attention for Object Recognition in Spatial 3D Data, in: Proceedings of 2nd International Workshop on Attention and Performance in Computational Vision (WAPCV '04), Paletta, L., Tsotsos, J.K., Rome, E., and Humphreys, G. (Eds), ISBN 3-540-24421-2, Revised Selected Papers Series: Lecture Notes in Computer Science, Vol. 3368. Conference: Prague, Czech Republic, May 15, 2004, [Get Paper (PDF)].

Abstract: In this paper, we present a new recognition system for the fast detection and classification of objects in spatial 3D data. The system consists of two main components: A biologically motivated attention system and a fast classifier. Input is provided by a 3D laser scanner, mounted on an autonomous mobile robot, that acquires illumination independent range and reflectance data. These are rendered into images and fed into the attention system that detects regions of potential interest. The classifier is applied only to a region of interest, yielding a significantly faster classification that requires only 30% of the time of an exhaustive search. Furthermore, both the attention and the classification system benefit from the fusion of the bi-modal data, considering more object properties for the detection of regions of interest and a lower false detection rate in classification.

Andreas Nüchter, Hartmut Surmann, Kai Lingemann, Joachim Hertzberg, and Sebastian Thrun. 6D SLAM with Application in Autonomous Mine Mapping, in Proceedings IEEE 2004 International Conference Robotics and Automation (ICRA '04), New Orleans, USA, Omnipress, ISBN 0-7803-8233-1, pages 1998 - 2003, April 2004, [Get Paper (PDF)] [HTML version] [Get Video].

Abstract: To create with an autonomous mobile robot a 3D volumetric map of a scene it is necessary to gage several 3D scans and to merge them into one consistent 3D model. This paper provides a new solution to the simultaneous localization and mapping (SLAM) problem with six degrees of freedom. Robot motion on natural surfaces has to cope with yaw, pitch and roll angles, turning pose estimation into a problem in six mathematical dimensions. A fast variant of the Iterative Closest Points algorithm registers the 3D scans in a common coordinate system and relocalizes the robot. Finally, consistent 3D maps are generated using a global relaxation. The algorithms have been tested with 3D scans taken in the Mathies mine, Pittsburgh, PA. Abandoned mines pose significant problems to society, yet a large fraction of them lack accurate 3D maps.

Dominik Giel, Susanne Frey, Andrea Thelen, Jens Bongartz, Peter Hering, Andreas Nüchter, Hartmut Surmann, Kai Lingemann, and Joachim Hertzberg. Ultra-fast holographic recording and automatic 3D scan matching of living human faces, in PERSPECTIVE IN IMAGE-GUIDED SURGERY, Proceedings of the Scientific Workshop Medical Robotics, Navigation and Visualization (MRNV '04), World Scientific, ISBN 981-238-872-9, Book of Abstracts: ISBN 3-9807690-5-4 (Kreative Konzepte, Remagen), Remagen, Germany, March 2004 [Get Paper (PDF)] [HTML version]

Abstract: 3D models of the skin surface of patients are created by ultra-fast holography and automatic scan matching of synchronously recorded holograms. By recording with a pulsed laser and continuous-wave optical reconstruction of the holographic real image, motion artifacts are eliminated. Focal analys is of the real image yields a surface relief of the patient. To generate a complete 360 patient model, several synchronously recorded reliefs are registered by automatic scan matching. We find the transformation consisting of a rotation and a translation that minimizes a cost function containing the Euclidian distances between points pairs from two surface relief maps. A variant of the ICP (Iterative Closest Points) algorithm2 is used to compute such a minimum. We propose a new fast approximation based on kDtrees for the problem of creating the closest point pairs on which the ICP algorithm spends most of its time.

Andreas Nüchter, Hartmut Surmann, and Joachim Hertzberg. Automatic Classification of Objects in 3D Laser Range Scans, in Proceedings of the 8th Conference on Intelligent Autonomous Systems (IAS '04), IOS Press, ISBN 1-58603-414-6, pages 963 - 970, Amsterdam, The Netherlands, March 2004, [Get Paper (PDF)] [HTML version].

Abstract: This paper presents a new method for object detection and classification in 3D laser range data that is acquired by an autonomous mobile robot. Off-screen rendered depth and reflectance images serve as an input for an Ada Boost learning procedure that constructs a cascade of classifiers. The performance of the classification is improved by combining both sensor modalities, which are independent from external light. The resulting approach for object classification is real-time capable and reliable. It combines recent results in computer vision with the emerging technology of 3D laser scanners.

Andreas Nüchter. Schnelle Visualisierung von Radialen 3D-Laserscans in Proceedings of the 5. Fachwissenschaftlicher Informatikkongress - Informatiktage 2003, ISBN 3-920560-21-3, pages 243 - 246, Bad Schussenried, Germany, November 2003 (2004).

Andreas Nüchter, Hartmut Surmann, Kai Lingemann, and Joachim Hertzberg. Semantic Scene Analysis of Scanned 3D Indoor Environments, in Proceedings of the 8th International Fall Workshop Vision, Modeling, and Visualization 2003 (VMV '03), IOS Press, ISBN 3-89838-048-3, pages 215 - 222, Munich, Germany, November 2003, [Get Paper (PDF)] [HTML Version].

Abstract: Precise digital 3D models of indoor environments are needed in several applications, e.g., facility management, architecture, rescue and inspection robotics. This paper presents a new method that transforms a 3D volumetric model, acquired by a mobile robot equipped with a 3D laser scanner, into a very precise compact 3D map and generates semantic descriptions. The scanned 3D scene is matched against a coarse semantic description of general indoor environments. The matching is done by a Prolog program compiled from the scanned 3D scene and combined with clauses from the coarse semantic description. The generated scene specific knowledge produced by the unification in the Prolog program is used to refine the 3D model.

Andreas Nüchter, Hartmut Surmann, Kai Lingemann, Kai Pervölz, and Joachim Hertzberg. Video: Autonomous Mobile Robots for 3D Digitalization of Environments, in Video Theatre of the 4th IEEE International Conference on Recent Advances in 3D Digital Imaging and Modeling (3DIM '03), Banff, Canada, October 2003, [Download Video].

Johannes Schauer and Andreas Nü Joachim Hertzberg. Automatic Model Refinement for 3D Reconstruction with Mobile Robots, in Proceedings of the 4th IEEE International Conference on Recent Advances in 3D Digital Imaging and Modeling (3DIM '03), IEEE Computer Society Press, ISBN 0-7695-1991-1, pages 394 - 401, Banff, Canada, October 2003, [Get Paper (PDF)] [HTML Version].

Abstract: Precise digital 3D models of indoor environments are needed in several applications, e.g., facility management, architecture, rescue and inspection robotics. This paper presents a new algorithm that transforms a 3D volumetric model into a very precise compact 3D map and generates semantic descri ptions. Our system is composed of a robust, autonomous mobile robot for the automatic data acquisition and a precise, cost effective, high quality 3 D laser scanner to gage indoor environments. The reconstruction method consists of reliable scan matching and feature detection algorithms. The 3D scene is matched against a coarse semantic description of general indoor environments and the generated knowledge is used to refine the 3D model.

Andreas Nüchter, Hartmut Surmann, Kai Lingemann, Joachim Hertzberg: Consistent 3D Model Construction with Autonomous Mobile Robots in: A. Günter et al. (eds.): KI 2003: Advances in Artificial Intelligence. 26th Annual German Conference on AI, Proceedings Springer LNAI vol. 2821, ISBN 3-540-20059-2, pages 550 - 564, Hamburg, Germany, September 2003, [Get Paper (PDF)] [HTML Version].

Abstract: Digital 3D models of the environment are needed in facility management, architecture, rescue and inspection robotics. To create 3D volumet ric models of scenes, rooms or buildings, it is necessary to gage several 3D scans and to merge them into one consistent 3D model. This paper presen ts a system, composed of a fast and robust, autonomous mobile robot, a precise, cost effective, high quality 3D laser scanner, and reliable scan mat ching algorithms for measuring and reconstructing environments, capable of matching two 3D scans within a fraction of a second. The proposed new sof tware modules for scan matching are fast variants of the iterative closest point algorithm (ICP) for consistent alignment. Two applications are presented: First, the reconstruction of an office environment, second, the fitting of sewer pipes into 3D data to detect deviations from the spatial geometry.

Andreas Nüchter, Hartmut Surmann, and Joachim Hertzberg. Planning Robot Motion for 3D Digitalization of Indoor Environments, in Proceedings of the 11th International Conference on Advanced Robotics (ICAR '03), pages 222 - 227, ISBN 972-96889-9-0, Coimbra, Portugal, June 2003, [Get Paper (PDF)] [HTML Version].

Abstract: 3D digitalization of environments without occlusions requires multiple 3D scans. Autonomous mobile robots equipped with a 3D laser scanner are wel l suited for the gaging task. They need an efficient exploration scheme for the digitalization. We present a new approach for planning the next scan pose as well as the robot motion. Our approach calculates a collision free trajectory regarding complicated objects, e.g., with jutting out edges. A closed loop and global ly stable motor control ler navigates the mobile robot. The results of a 3D digitalization experiment in the main hall of castle Birlinghoven is presented.

Simone Frintrop, Erich Rome, Andreas Nüchter, and Hartmut Surmann. An Attentive, Multi-modal Laser Eye, in Proceedings of the third International Conference on Computer Vision Systems (ICVS '03)., J. Crowley, J.H. Piater, M. Vincze, and L. Paletta (eds), pages 202 - 211, Springer LNCS 2626, ISBN 3-540-00921-3, Graz, Austria, April 2003, [Get Paper (PDF)] (copyright Springer Verlag).

Abstract: In this paper we present experimental results on a novel application of visual attention mechanisms for the selection of points of interes t in an arbitrary scene. The imaging sensor used is a multi-modal 3D laser scanner. In a single 3D scan pass, it is capable of providing range data as well as a gray-scale intensity image. The scanner is mounted on top of an autonomous mobile robot and serves control purposes. We present results achieved by applying the visual attention system of Itti et al. [8] to recorded scans of indoor and outdoor scenes. The vast ma jority of the prima ry attended locations pointed to scene ob jects of potential interest for navigation and ob ject detection tasks. Moreover, both sensor modalities c omplement each other, resulting in a greater variety of points of interest than one modality alone can provide.

Simone Frintrop, Erich Rome, Andreas Nüchter, and Hartmut Surmann. Applying Attentional Mechanisms to Bi-modal 3D Laser Data, in International Workshop on Attention and Performance in Computer Vision (WAPCV '03) L. Paletta, G.W. Humphreys, and R.B. Fisher (eds), pages. 25-30, Joanneum Research, Graz, Austria, 2003, [Get Paper (PDF)].

Abstract: In this paper we present experimental results on a novel application of visual attention mechanisms for the selection of points of interest in an ar bitrary scene. The imaging sensor used is a multi-modal 3D laser scanner. In a single 3D scan pass, it is capable of providing range data as well as a gray-scale intensity image. The scanner is mounted on top of an autonomous mobile robot and serves control purposes. We present results achieved by applying the visual attention system of Itti et al. [8] to recorded scans of indoor and outdoor scenes. The vast majority of the primary attended l ocations pointed to scene objects of potential i nterest for navigation and object detection tasks. Moreover, both sensor modalities complement each other, resulting in a greater variety of points of interest than one modality alone can provide.

Andreas Nüchter. Autonome Exploration und 3D-Modellierung der Umgebung eines Roboters in Proceedings of the 4. Fachwissenschaftlicher Informatikkongress - Informatiktage 2002, pages 64 - 68, ISBN 3-920560-17-5, Bad Schussenried, Germany, November 2002 (2003), (best paper award) [Get Paper (PDF)].

Zusammenfassung: Autonome mobile Roboter müssen in der Lage sein, sicher durch ihre Umgebung zu navigieren, um anwendungsspezifische Aufgaben ausführen zu können. Gelingen kann dies nur durch den Einsatz von 3D-Sensoren und 3D-Karten. Daher ist die automatische und schnelle 3D-Modellierung der Umgebung eine wichtige Fragestellung in der Robotik. 3D-Laserscanner sind eine junge Technologie, die die Erfassung räumlicher Daten revolutioniert und Robotern das dreidimensionale Abtasten von Objekten mölich macht. Die vorliegende Arbeit untersucht und evaluiert die zur autonome n 3D-Kartenerstellung notwendigen Algorithmen mit Hilfe des AIS 3D-Laserscanners, der sich auf einer geeigneten Roboterplattform befindet. Das entwickelte System ermöglicht das berhrungslose Abtasten der gesamten Umgebung. Dafür werden mehrere 3D-Scans zu einer konsistenten Szene zusammengefügt sowie Scanpositionen generiert.

Hartmut Surmann, Kai Lingemann, Andreas Nüchter, and Joachim Hertzberg. Fast acquiring and analysis of three dimensional laser range data, in Proceedings of the 6th International Fall Workshop Vision, Modelling, and Visualization 2001 (VMV '01), pages 59 - 66, ISBN 3-89838-028-9, Stuttgart, Germany, November 2001, [Get Paper (PDF)] [HTML Version].

Abstract: This paper presents a precise (1cm), lightweight (5kg) and low cost 3D laser range finder for the fast gaging (1.4 sec) of environments. Real-time algorithms for the data reduction, 3D-object segmentation are also presented. A special designed suspension unit, a standard servo motor and a stan dard 2D range finder are used to build the 3D scanner. Maximal resolutions e.g. 180 (h) 90 (v) degree with 194400 points are grabbed in 8.1 seconds and low resolutions with 16200 points are grabbed in 1.4 seconds. While scanning, different online algorithms for line and surface detection are applied to the data. 3D-Object segmentation and detection are done offline after the scan. With the proposed approach, a precise, reliable, mobile, low cost, and real-time capable 3D sensor for the contact-less measuring of environments without additional landmarks is available.

Andreas Nüchter, Kai Lingemann. Ein 3D Laserscanner für autonome mobile Roboter, in Proceedings of the 3. Fachwissenschaftlicher Informatikkongress - Informatiktage 2001, pages 89 - 92, Bad Schussenried, Germany, November 2001 (2002), [Get Paper (PDF)].

Hartmut Surmann, Kai Lingemann, Andreas Nüchter, and Joachim Hertzberg. A 3D laser range finder for autonomous mobile robots, in Proceedings of the 32nd International Symposium on Robotics (ISR '01), pages 153 - 158, ISBN 89-88366-04-2, Seoul, Korea, May 2001, [Get Paper (PDF)].

Abstract: This paper presents a high quality, low cost 3D laser range finder designed for autonomous mobile systems. The 3D laser is built on the bas e of a 2D range finder by the extension with a standard servo. The servo is controlled by a computer running RT-Linux. The scan resolution (5 cm) f or a complete 3D scan of an area of 150 (h) 90 (v) degree is up to 115000 points and can be grabbed in 12 seconds. Standard resolutions e.g. 150 (h) 90 (v) degree with 22500 points are grabbed in 4 seconds. While scanning, different online algorithms for line and surface detection are applied to the data. Object segmentation and detection are done offline after the scan. The implemented software modules detect overhanging objects blocking t he path of the robot. With the proposed approach a cheap, precise, reliable and real-time capable 3D sensor for autonomous mobile robots is availabl e and the robot navigation and recognition in real-time is improved. 1. Introduction Prognoses at the beginning of the nineties claimed for the new millennium a number of about 50.000 independently operating autonomous service robots in different areas of production and service sectors [1]. The reality is different. In industrial environments guided vehicles, i.e. vehicles guided by a magnetic or optical track are standard [2]. Autonomous mobile service systems, i.e. systems not restricted by a track, are used extremely rarely although many research groups are working on this since sev eral years particularly with mobile systems for transportation tasks, e.g. [3, 4, 5, 6]. One of several reasons for the gap between prognoses and r eality is the lack of good, cheap and fast sensors that allow the robots to sense the environment in real-time and to act on the basis of the acquir ed data. This paper presents a 3D laser range finder designed for autonomous mobile systems (fig. 1). A large number of today's autonomous robots us e 2D laser range finders as a proximity sensor. They are very fast (processing time 30 ms), precise ( 1 cm, ) and becoming cheaper ($3000) since th ere are at least two competing products [7, 8].

Ming Li, Wei Li, Jian Wang, Qingquan Li, and Andreas Nüchter Towards Reliable Object Anchoring in Highly Dynamic Traffic Scenes in ICRA 2012 WORKSHOP Semantic Perception and Mapping for Knowledge-enabled Service Robotics (with interactive session and demonstrations), St. Paul, MN, USA, May 2012.

Dorit Borrmann, Jan Elseberg, and Andreas Nüchter. Thermal 3D Mapping for Saving Energy. Proceedings of the 5th International Conference on Cognitive Systems (COGSYS '12), [Get Poster (PDF)].

Martin Magnusson, Andreas Nüchter, Christopher Lörken, Achim J. Lilienthal, and Joachim Hertzberg. 3D Mapping the Kvarntorp Mine: A Field Experiment for Evaluation of 3D Scan Matching Algorithms. In Proceedings of the Workshop on 3D-Mapping at the IEEE International Conference on Intelligent Robots and Systems (IROS '08), Nice, France, September 2008.

Thomas Wiemann, Andreas Nüchter, Kai Lingemann, Stefan Stiene, and Joachim Hertzberg. Surface Reconstruction for 3D Robotic Mapping. In Proceedings of the Workshop on 3D-Mapping at the IEEE International Conference on Intelligent Robots and Systems (IROS '08), Nice, France, September 2008.

Stefan Stiene, Andreas Nüchter, Kai Lingemann, and Joachim Hertzberg. An Experiment in Semantic Correction of Sensor Data, (Poster) in Proceedings Workshop on Semantic Information in Robotics at the IEEE International Conference Robotics and Automation (ICRA '07), Rome, Italy, April 2007, [Get Paper (PDF)].

Johannes Steger, Robert Märtin, Kai Lingemann, Andreas Nüchter, Joachim Hertzberg, and Peter König. Laser range scans of natural scenes for the evaluation of stereo- matching algorithms. Poster at ICVS Workshop From Computational Cognitive Neuroscience to Computer Vision (CCNCV '07) Bielefeld, Germany, March 2007.

Johannes Steger, Robert Märtin, Kai Lingemann, Andreas Nüchter, Joachim Hertzberg, and Peter König. Assessing stereo matching algorithms using ground-truth disparity maps of natural scenes, (Poster), in Proceedings of the 7th Meeting of the German Neuroscience Society / 31th Göttingen Neurobiology Conference, Neuroforum 2007, Göttingen, Germany, 2007.

Simone Frintrop, Erich Rome, Andreas Nüchter, and Hartmut Surmann, Focussing Object Recognition on Regions of Interest, in Proceedings of the 7. Tübingen Perception Conference (TWK '04), H. Bülthoff, H.A. Mallot, R. Ulrich, F.A. Wichmann (eds), page 67, Tübingen, Germany, February, 2004.

Simone Frintrop, Erich Rome, Andreas Nüchter, and Hartmut Surmann, Visuelle Aufmerksamkeitsmechanismen auf bimodalen Laserdaten, in Beiträge zur 6. Tübinger Wahrnehmungskonferenz (TWK '03), H. Bülthoff, K.R. Gegenfurtner, H.A. Mallot, R. Ulrich, F.A. Wichmann (eds), page 100, Tübingen, Germany, February, 2003.

Kai Lingemann, Andreas Nüchter, Joachim Hertzberg, Oliver Wulf, Bernardo Wagner, Kai Pervölz, Hartmut Surmann, and Thomas Christaller. RoboCupRescue2006 – Robot League, Deutschland1 (Germany), in Team Description Paper, Rescue Robot League Competition, (CDROM Proceedings), Bremen, Germany, June 2006, [Get Paper (PDF)].

Abstract: After scoring second in RoboCup Rescue 2004 with Kurt3D and participating in 2005 with two robots, namely Kurt3D and RTS Crawler, we concentrated on the development of interaction between both vehicles. Kurt3D is able to autonomously explore and map the environment in 3D and search for victims. The RTS Crawler is designed to access more demanding territory (i.e., red arena), working either remote controlled or semi-autonomous. The key innovation of this system lies in the capability for autonomous 6D SLAM (simultaneous localization and mapping) and 3D map generation of natural scenes, combined with the intelligent cooperation between robots that enables one operator to efficiently map and explore the whole arena.
The robots are equipped with dedicated state of the art equipment, e.g., 3D laser range finders, infrared camera and CO2-sensor. Robots as well as operator station are rather compact and easy to set up. The challenge of controlling two rescue robots with only one operator is managed with a redesigned user interface and a number of autonomous and semi-autonomous features.

Andreas Nüchter, Kai Lingemann, and Joachim Hertzberg. Kurt3D – A Mobile Robot for 3D Mapping of Environments, ELROB Technical Paper, Hammelburg, Germany, May 2006. [Get Technical Paper (PDF)] [Get Team Information (PDF)] [Get Vehicle Specification Sheet (PDF)] [Get Team Roster (PDF)].

Abstract: The mobile robot Kurt3D is the first robot that is capable of mapping its environment in 3D and self localize in all six degrees of freedom, i.e., considering its x, y and z positions and the roll, yaw and pitch angles. Robot motion on natural surfaces has to cope with yaw, pitch and roll angles, turning pose estimation into a problem in six mathematical dimensions. Kurt3D creates a consistent volumetric scene in a common coordinate frame from multiple 3D laser scans. To create 3D volumetric maps it is necessary to gage several 3D scans and register them into one consistent 3D model. A fast variant of the Iterative Closest Points (ICP) algorithm is used for registration and relocalization.

Hartmut Surmann, Kai Lingemann, Andreas Nüchter, Matthias Hennig, Kai Pervölz, Oliver Wulf, Joachim Hertzberg, Bernardo Wagner, and Thomas Christaller. RoboCupRescue - Robot League Team, Team Deutschland1 (Germany) Team Description Paper, Rescue Robot League Competition, (RoboCup 2005), (CDRom Proceedings), Osaka, Japan, July 2005, (6th place), [Get Paper (PDF)].

Abstract: After the second place in RoboCup Rescue 2004, a new version of the mobile robot Kurt3D was developed in our groups during the last year [1]. The key innovation of this system lies in the capability for autonomous or operator-assisted 6D SLAM (simultaneous localization and mapping) and 3D map generation of natural scenes. Hence, Kurt3D already meets the basic requirement regarding urban search and rescue. For the rescue robot league competition, it is additionally configured with dedicated state-of-the-art equipment e.g. infrared camera and CO2sensor. The robot and the operator station are rather compact and easy to set up. The operator uses a joystick as a remote control for the robot and can watch a live video of the scene where the robot drives. Data are transmitted via wireless LAN. A 3D laser scanner, which is mounted on an outdoor variant of Kurt3D, is used as the main sensor for map generation as well as for navigation and localization. The whole system has been used with a proven record of success for different tasks of map building, so that we are confident of managing the rescue robot league competition, too.

Hartmut Surmann, Rainer Worst, Matthias Hennig, Kai Lingemann, Andreas Nüchter, Kai Pervoelz, Kiran Raj Tiruchinapalli, Thomas Christaller, and Joachim Hertzberg. RoboCup Rescue - Robot League Team KURT3D, Germany, Team Description Paper, Rescue Robot League Competition (CDROM Proceedings RoboCup 2004), Portugal, July 2004, (vice world champion), [Get Paper].

Abstract: A mobile robot named KURT3D was developed at the Fraunhofer Institute for Autonomous Intelligent Systems during the last three years. The key innovation of this system lies in the capability for autonomous or operatorassisted 6D SLAM (simultaneous localization and mapping) and 3D map generation of natural scenes. Hence, KURT3D already meets the basic requirement regarding urban search and rescue. For the rescue robot league competition, it is additionally configured with dedicated state-of-the-art equipment. The robot and the operator station are rather compact and easy to set up. The operator uses a joystick as a remote control for the robot and can watch a live video of the scene where the robot drives. Data are transmitted via wireless LAN. A 3D laser scanner, which is mounted on an outdoor variant of KURT3D, is used as the main sensor for map generation as well as for navigation and localization. The whole system has been used with a proven record of success for different tasks of map building, so that we a reconfident of managing the rescue robot league competition, too.

Hartmut Surmann, Andreas Nüchter, and Joachim Hertzberg. Autonomous Mobile Robots for 3D Digitalization of Indoor Environments, GMD Report 147, ISSN 1435-2702, Sankt-Augustin, Germany, 2003.

Andreas Nüchter. Autonome Exploration und Modellierung von 3D-Umgebungen Diplomarbeit an der Universität Bonn, Bonn, Germany Juli 2002, also appeared as GMD-Report 157, ISBN 3-88457-979-7, Sankt Augustin, Germany, July 2002, [Get Paper (PDF)] [HTML Version].

Zusammenfassung: Autonome mobile Roboter müssen in der Lage sein, sicher durch ihre Umgebung zu navigieren, um anwendungsspezifische Aufgaben ausführen zu können. Gelingen kann dies nur durch den Einsatz von 3D-Sensoren und 3D-Karten. Daher ist die automatische und schnelle Modellierung der Umgebung eine wichtige Fragestellung in der Robotik. 3D-Laserscanner sind eine junge Technologie, die die Erfassung räumlicher Daten revolutioniert und Robotern das dreidimensionale Abtasten von Objekten möglich macht. Die vorliegende Arbeit untersucht und evaluiert die zur autonomen 3D-Kartenerstellung notwendigen Algorithmen mit Hilfe des AIS 3D-Laserscanners, der sich auf einer geeigneten Roboterplattform befindet. Das entwickelte System ermöglicht dabei das berührungslose Abtasten der gesamten Umgebung. Der erste Teil der Arbeit beschäftigt sich mit der Aufgabe, 3D-Scans in einem globalen Koordinatensystem zu registrieren. Die von der Odometrie des Roboters geschätzte Pose (Position a und Orientierung) wird dabei korrigiert. Verschiedene Variationen des iterativen Algorithmus der nächsten Punkte (ICP) kommen zum Einsatz. Im zweiten Teil geht es darum, eine möglichst optimale nächste Scanposition zu bestimmen, von der aus unbekanntes Terrain erforscht werden kann. Ein randomisierter Approximationsalgorithmus plant die neue Posi tion des Scanners. Anschliessend ist diese Position durch eine geeignete Motorregelung anzufahren, wobei Kollisionsvermeidung berucksichtigt wird. Schliesslich werden die Ergebnisse in geeigneter Weise, unter anderem durch Gittermodelle, visualisiert. Schlagwörter: 3D-Laserscanner, 3D-Modellierung, 3D-Kartenerstellung, Scanmatching, iterativer Algorithmus der nchsten Punkte, autonome Exploration, simultanes Lokalisationsa und Kartierungsproblem, Approximation der nächsten optimalen Scanposition, Robotersteuerung, Oberflächenreprsentation durch Gittermodelle.

Hartmut Surmann, Kai Lingemann, Andreas Nüchter, and Joachim Hertzberg. Aufbau eines 3D-Laserscanners für autonome mobile Roboter, GMD-Report 126, ISBN 3-88457-974-6, Sankt Augustin, Germany, March 2001, [Abstract] [Get Paper (PDF)] [HTML Version].

Zusammenfassung: Diese Ausarbeitung stellt das Konzept und die Realisierung eines 3D-Laserscanners vor. Ziel der Realisierung war es, das Dreieck aus Kosten, Geschwindigkeit und Qualität so zu optimieren, dass der 3D-Scanner auf autonomen mobilen Robotern sinnvoll zur Exploration und Navigation eingesetzt werden kann. Ein auf autonomen mobile Fahrzeugen häufig verwendeter 2D-Laserscanner wurde dazu mittels einer selbst konstruierten Aufhängung und eines Servomotors aufgerüstet. Mittels des auf einem Standardrechner laufenden Echtzeitbetriebssystem RT-Linux steuert der Servomotor den 3D Laserscanner direkt an. Unterschiedliche Online-Algorithmen zur Linienerkennung und Flächendetektion bilden die Software-Basis des 3D Scanners. Offline-Algorithmen zur Objektsegmentierung und Erkennung sowie ein 3D-Visualisierungsprogramm runden das Softwarepaket ab.