Publications

•   Jörg Müller. Autonomous Navigation for Miniature Indoor Airships. PhD thesis, Albert-Ludwigs-University of Freiburg, Department of Computer Science, June 2013. [ bib | .pdf ]
•   Jürgen Hess, Maximilian Beinhofer, Daniel Kuhner, Philipp Ruchti, and Wolfram Burgard. Poisson-driven dirt maps for efficient robot cleaning. In Proc. of the IEEE Int. Conf. on Robotics & Automation (ICRA), Karlsruhe, Germany, May 2013. [ bib | .pdf ]
•   J. Meyer, M. Kuderer, J. Müller, and W. Burgard. Online marker labeling for automatic skeleton tracking in optical motion capture. In Proceedings of the ICRA Workshop on Computational Techniques in Natural Motion Analysis and Reconstruction, Karlsruhe, Germany, May 2013. [ bib ]
•   Rainer Kümmerle. State Estimation and Optimization for Mobile Robot Navigation. PhD thesis, Albert-Ludwigs-University of Freiburg, Department of Computer Science, April 2013. [ bib | .pdf ]
•   A. Riefert, J. Müller, M. Sauer, W. Burgard, and B. Becker. Identification of critical variables using an FPGA-based fault injection framework. In Proceedings of the IEEE VLSI Test Symposium (VTS), Berkeley, CA, USA, April 2013. [ bib ]
•   Bastian Steder. Feature-Based 3D Perception for Mobile Robots. PhD thesis, Albert-Ludwigs-University of Freiburg, Department of Computer Science, April 2013. [ bib | .pdf ]
•   A. Riefert, J. Müller, M. Sauer, W. Burgard, and B. Becker. Identification of critical variables using an FPGA-based fault injection framework. In Proceedings of the Workshop Testmethoden und Zuverlässigkeit von Schaltungen und Systemen (TUZ), Dresden, Germany, February 2013. [ bib ]
•   Henrik Kretzschmar, Markus Kuderer, and Wolfram Burgard. Inferring navigation policies for mobile robots from demonstrations. In In Proc. of the Autonomous Learning Workshop at the IEEE International Conference on Robotics and Automation (ICRA), Karlsruhe, Germany, 2013. [ bib ]
•   Maximilian Beinhofer, Henrik Kretzschmar, and Wolfram Burgard. Deploying artificial landmarks to foster data association in simultaneous localization and mapping. In Proc. of the IEEE International Conference on Robotics and Automation (ICRA), Karlsruhe, Germany, 2013. [ bib | .pdf ]
•   M. Beinhofer, J. Müller, and W. Burgard. Effective landmark placement for accurate and reliable mobile robot navigation. Robotics & Autonomous Systems, 2013. [ bib | DOI | http ]
•   F. Höflinger, J. Müller, R. Zhang, W. Burgard, and L.M. Reindl. A wireless micro inertial measurement unit (IMU). IEEE Transactions on Instrumentation & Measurement, 2013. Accepted for publication. [ bib ]
•   J. Müller and W. Burgard. Efficient probabilistic localization for autonomous indoor airships using sonar, air flow, and IMU sensors. Advanced Robotics, 27(9):711-724, 2013. [ bib | DOI ]
•   F. Sittel, J. Müller, and W. Burgard. Computing velocities and accelerations from a pose time sequence in three-dimensional space. Technical Report 272, University of Freiburg, Department of Computer Science, 2013. [ bib | .pdf ]
•   W. Burgard and C. Stachniss. Gestatten, obelix! Forschung - Das Magazin der Deutschen Forschungsgemeinschaft, 1, 2013. In German, invited. [ bib | .pdf ]
•   A. Hornung, K.M. Wurm, M. Bennewitz, C. Stachniss, and W. Burgard. OctoMap: An efficient probabilistic 3d mapping framework based on octrees. Autonomous Robots, 34:189-206, 2013. [ bib | .pdf ]
•   D. Maier, C. Stachniss, and M. Bennewitz. Vision-based humanoid navigation using self-supervised obstacle detection. The Int. Journal of Humanoid Robotics (IJHR), 2013. In press. [ bib | .pdf ]
•   K.M. Wurm, C. Dornhege, B. Nebel, W. Burgard, and C. Stachniss. Coordinating heterogeneous teams of robots using temporal symbolic planning. Autonomous Robots, 2013. In press. [ bib | .pdf ]
•   K.M. Wurm, H. Kretzschmar, R. Kümmerle, C. Stachniss, and W. Burgard. Identifying vegetation from laser data in structured outdoor environments. Robotics & Autonomous Systems, 2013. In press. [ bib | .pdf ]
•   N. Abdo, H. Kretzschmar, L. Spinello, and C. Stachniss. Learning manipulation actions from a few demonstrations. In Proc. of the IEEE International Conference on Robotics & Automation (ICRA), Karlsruhe, Germany, 2013. [ bib | .pdf ]
•   P. Agarwal, G.D. Tipaldi, L. Spinello, C. Stachniss, and W. Burgard. Robust map optimization using dynamic covariance scaling. In Proc. of the IEEE International Conference on Robotics & Automation (ICRA), Karlsruhe, Germany, 2013. [ bib | .pdf ]
•   R. Kümmerle, M. Ruhnke, B. Steder, C. Stachniss, and W. Burgard. A navigation system for robots operating in crowded urban environments. In Proc. of the IEEE Int. Conf. on Robotics & Automation (ICRA), 2013. [ bib | .pdf ]
•   J. Wendeberg, J. Müller, C. Schindelhauer, and W. Burgard. Robust tracking of a mobile beacon using time differences of arrival with simultaneous calibration of receiver positions. In Proceedings of the International Conference on Indoor Positioning and Indoor Navigation (IPIN), Sydney, Australia, November 2012. [ bib | .pdf ]
•   G. Grisetti, R. Kümmerle, and K. Ni. Robust optimization of factor graphs by using condensed measurements. In Proc. of the IEEE/RSJ Int. Conf. on Intelligent Robots and Systems (IROS), Vilamoura, Portugal, October 2012. [ bib | .pdf ]
•   Kai M. Wurm. Techniques for Multi-Robot Coordination and Navigation. PhD thesis, Albert-Ludwigs-University of Freiburg, Department of Computer Science, October 2012. [ bib | http ]
•   C. Stachniss, K. Schill, and D. Uttal, editors. Spatial Cognition VIII. Springer, August 2012. [ bib ]
•   D. Meyer-Delius, M. Beinhofer, and W. Burgard. Occupancy grid models for robot mapping in changing environments. In Proc. of the AAAI Conf. on Artificial Intelligence (AAAI), Toronto, Canada, July 2012. [ bib | .pdf ]
•   M. Ruhnke, R. Kümmerle, G. Grisetti, and W. Burgard. Highly accurate 3d surface models by sparse surface adjustment. In Proc. of the IEEE Int. Conf. on Robotics and Automation (ICRA), St. Paul, MN, USA, May 2012. [ bib | .pdf ]
•   J. Müller, O. Paul, and W. Burgard. Probabilistic velocity estimation for autonomous miniature airships using thermal air flow sensors. In Proc. of the IEEE International Conference on Robotics & Automation (ICRA), pages 39-44, Saint Paul, MN, USA, May 2012. [ bib | .pdf ]
•   F. Höflinger, J. Müller, M. Törk, L.M. Reindl, and W. Burgard. A wireless micro inertial measurement unit (IMU). In Proceedings of the IEEE International Instrumentation and Measurement Technology Conference (I2MTC), pages 2578-2583, Graz, Austria, May 2012. [ bib | DOI | .pdf ]
•   C. Sprunk, B. Lau, and W. Burgard. Improved non-linear spline fitting for teaching trajectories to mobile robots. In Proc. of the IEEE International Conference on Robotics and Automation (ICRA), pages 2068-2073, St. Paul, MN, USA, May 2012. [ bib | .pdf ]
•   S. Grzonka, A. Karwath, F. Dijoux, and W. Burgard. Activity-based Indoor Mapping and Estimation of Human Trajectories. IEEE Transactions on Robotics (T-RO), 8(1):234-245, 2 2012. [ bib ]
•   S. Grzonka, G. Grisetti, and W. Burgard. A Fully Autonomous Indoor Quadrotor. IEEE Transactions on Robotics (T-RO), 8(1):90-100, 2 2012. [ bib ]
•   J. Hess, D. Tipaldi, and W. Burgard. Null space optimization for effective coverage of 3d surfaces using redundant manipulators. In Proc. of the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), pages 1923-1928, 2012. [ bib | DOI | .pdf ]
Keywords: Cost function;End effectors;Joints;Kinematics;Surface treatment;
•   Dominik Joho, Gian Diego Tipaldi, Nikolas Engelhard, Cyrill Stachniss, and Wolfram Burgard. Unsupervised scene analysis and reconstruction using nonparametric Bayesian models. In Proc. of the Workshop on Robots in Clutter at Robotics: Science and Systems (RSS), Sydney, Australia, 2012. [ bib ]
•   Markus Kuderer, Henrik Kretzschmar, Christoph Sprunk, and Wolfram Burgard. Feature-based prediction of trajectories for socially compliant navigation. In Proc. of Robotics: Science and Systems (RSS), Sydney, Australia, 2012. [ bib | .pdf ]
•   K. M. Wurm, H. Kretzschmar, R. Kümmerle, C. Stachniss, and W. Burgard. Identifying vegetation from laser data in structured outdoor environments. Robotics and Autonomous Systems, (0):-, 2012. In Press. [ bib | DOI | .pdf ]
•   R. Kümmerle, G. Grisetti, and W. Burgard. Simultaneous parameter calibration, localization, and mapping. Advanced Robotics, 26(17):2021-2041, 2012. [ bib | DOI | .pdf ]
•   Kai O. Arras, Boris Lau, Slawomir Grzonka, Matthias Luber, Oscar Martinez Mozos, Daniel Meyer-Delius, and Wolfram Burgard. Range-based people detection and tracking for socially enabled service robots. In Erwin Prassler, Rainer Bischoff, Wolfram Burgard, Robert Haschke, Martin Hägele, Gisbert Lawitzky, Bernhard Nebel, Paul Plöger, Ulrich Reiser, and Marius Zöllner, editors, Towards Service Robots for Everyday in Environments, volume 76 of Springer Tracts in Advanced Robotics (STAR), pages 235-280. Springer, 2012. [ bib ]
•   H. Kretzschmar and C. Stachniss. Information-theoretic pose graph compression for laser-based SLAM. International Journal of Robotics Research (IJRR), 31:1219-1230, 2012. [ bib | .pdf ]
•   G. Grisetti, L. Iocchi, B. Leibe, V.A. Ziparo, and C. Stachniss. Digitization of inaccessible archeological sites with autonomous mobile robots. In Conf. on Robotics Innovation for Cultural Heritage, 2012. [ bib ]
•   J. Roewekaemper, C. Sprunk, G.D. Tipaldi, C. Stachniss, P. Pfaff, and W. Burgard. On the position accuracy of mobile robot localization based on particle filters combined with scan matching. In Proc. of the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2012. [ bib | .pdf ]
•   L. Spinello, C. Stachniss, and W. Burgard. Scene in the loop: Towards adaptation-by-tracking in rgb-d data. In Proc. of the RSS Workshop RGB-D: Advanced Reasoning with Depth Cameras, 2012. [ bib | .pdf ]
•   N. Abdo, H. Kretzschmar, and C. Stachniss. From low-level trajectory demonstrations to symbolic actions for planning. In Proc. of the ICAPS Workshop on Combining Task and Motion Planning for Real-World Applications (TAMPRA), 2012. [ bib | .pdf ]
•   D. Joho, G.D. Tipaldi, N. Engelhard, C. Stachniss, and W. Burgard. Nonparametric Bayesian models for unsupervised scene analysis and reconstruction. In Proc. of Robotics: Science and Systems (RSS), 2012. [ bib | .pdf ]
•   M. Ruhnke, B. Steder, G. Grisetti, and W. Burgard. 3D environment modeling based on surface primitives. Towards Service Robots for Everyday Environments, pages 281-300, 2012. [ bib ]
•   A. Cunningham, K.M. Wurm, W. Burgard, and F. Dellaert. Fully distributed scalable smoothing and mapping with robust multi-robot data association. In Proc. of the IEEE/RSJ International Conference on Robotics & Automation (ICRA), Saint Paul, MN, USA, 2012. [ bib ]
•   G. Tipaldi, D. Meyer-Delius, M. Beinhofer, and W. Burgard. Simultaneous localization and dynamic state estimation in reconfigurable environments. In Proc. of the IEEE/RSJ IROS Workshop on Metrics and Methodologies for Autonomous Robot Teams in Logistics (MMART-LoG), San Francisco, USA, October 2011. [ bib | .pdf ]
•   M. Ruhnke, R. Kümmerle, G. Grisetti, and W. Burgard. Range sensor based model construction by sparse surface adjustment. In Proc. of the IEEE Workshop on Advanced Robotics and its Social Impacts (ARSO), Half Moon Bay, CA, USA, October 2011. [ bib | .pdf ]
•   R. Kümmerle, G. Grisetti, and W. Burgard. Simultaneous calibration, localization, and mapping. In Proc. of the IEEE/RSJ Int. Conf. on Intelligent Robots and Systems (IROS), San Francisco, CA, USA, September 2011. [ bib | .pdf ]
•   M. Beinhofer, J. Müller, and W. Burgard. Landmark placement for accurate mobile robot navigation. In Proceedings of the European Conference on Mobile Robots (ECMR), pages 55-60, Örebro, Sweden, September 2011. [ bib | .pdf ]
•   J. Müller, N. Kohler, and W. Burgard. Autonomous miniature blimp navigation with online motion planning and re-planning. In Proc. of the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), pages 4941-4946, San Francisco, CA, USA, September 2011. [ bib | .pdf ]
•   Kai M. Wurm, Daniel Hennes, Dirk Holz, Radu B. Rusu, Cyrill Stachniss, Kurt Konolige, and Wolfram Burgard. Hierarchies of octrees for efficient 3d mapping. In Proc. of the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), San Francisco, CA, USA, September 2011. [ bib | .pdf ]
•   D. Meyer-Delius, M. Beinhofer, and W. Burgard. Grid-based models for dynamic environments. Technical report, Dept. of Computer Science, University of Freiburg, July 2011. [ bib | .pdf ]
•   M. Sauer, V. Tomashevich, J. Müller, M. Lewis, A. Spilla, I. Polian, B. Becker, and W. Burgard. An FPGA-based framework for run-time injection and analysis of soft errors in microprocessors. In Proceedings of the IEEE International On-Line Testing Symposium (IOLTS), pages 182-185, Athens, Greece, July 2011. [ bib | .pdf ]
•   D. Meyer-Delius, M. Beinhofer, A. Kleiner, and W. Burgard. Using artificial landmarks to reduce the ambiguity in the environment of a mobile robot. In Proc. of the IEEE Int. Conf. on Robotics and Automation (ICRA), pages 5173-5178, Shanghai, China, May 2011. [ bib | DOI | .pdf ]
•   Dominik Joho, Martin Senk, and Wolfram Burgard. Learning search heuristics for finding objects in structured environments. Robotics and Autonomous Systems, 59(5):319-328, May 2011. [ bib | DOI | .pdf ]
•   R. Kümmerle, G. Grisetti, H. Strasdat, K. Konolige, and W. Burgard. g2o: A general framework for graph optimization. In Proc. of the IEEE Int. Conf. on Robotics and Automation (ICRA), Shanghai, China, May 2011. [ bib | .pdf ]
•   M. Ruhnke, R. Kümmerle, G. Grisetti, and W. Burgard. Highly accurate maximum likelihood laser mapping by jointly optimizing laser points and robot poses. In Proc. of the IEEE Int. Conf. on Robotics and Automation (ICRA), Shanghai, China, May 2011. [ bib | .pdf ]
•   M. Beinhofer, J. Müller, and W. Burgard. Near-optimal landmark selection for mobile robot navigation. In Proc. of the IEEE International Conference on Robotics & Automation (ICRA), pages 4744-4749, Shanghai, China, May 2011. [ bib | .pdf ]
•   C. Sprunk, B. Lau, P. Pfaff, and W. Burgard. Online generation of kinodynamic trajectories for non-circular omnidirectional robots. In Proc. of the IEEE International Conference on Robotics and Automation (ICRA), pages 72-77, Shanghai, China, May 2011. [ bib | .pdf ]
•   A. Spilla, I. Polian, J. Müller, M. Lewis, V. Tomashevich, B. Becker, and W. Burgard. Run-time soft error injection and testing of a microprocessor using FPGAs. In Proceedings of the Workshop Testmethoden und Zuverlässigkeit von Schaltungen und Systemen (TUZ), Passau, Germany, February 2011. [ bib ]
•   Slawomir Grzonka. Mapping, State Estimation, and Navigation for Quadrotors and Human-Worn Sensor Systems. PhD thesis, Albert-Ludwigs-University of Freiburg, 2011. [ bib ]
•   S. Grzonka, B. Steder, and W. Burgard. 3D Place Recognition and Object Detection using a Small-sized Quadrotor. In Workshop on 3D Exploration, Mapping, and Surveillance with Aerial Robots at Robotics: Science and Systems (RSS), 2011. [ bib ]
•   S. Bouabdallah, C. Bermes, S. Grzonka, C. Gimkiewicz, A. Brenzikofer, R. Hahn, D. Schafroth, G. Grisetti, W. Burgard, and R. Siegwart. Towards Palm-Size Autonomous Helicopters. Journal of Intelligent & Robotic Systems, 61:1-27, 2011. [ bib ]
•   Boris Lau, Christoph Sprunk, and Wolfram Burgard. Incremental updates of configuration space representations for non-circular mobile robots with 2d, 2.5d, or 3d obstacle models. In European Conference on Mobile Robots (ECMR), pages 49-54, Örebro, Sweden, 2011. [ bib | .pdf ]
•   J. Sturm, C. Stachniss, and W. Burgard. A probabilistic framework for learning kinematic models of articulated objects. Journal on Artificial Intelligence Research, 41:477-526, 2011. [ bib | .pdf ]
•   M. Bennewitz, D. Maier, A. Hornung, and C. Stachniss. Integrated perception and navigation in complex indoor environments. In Proc. of the IEEE-RAS Int. Conf. on Humanoid Robots (HUMANOIDS), 2011. Invited presentation at the workshop on Humanoid service robot navigation in crowded and dynamic environments. [ bib ]
•   J. Becker, C. Bersch, D. Pangercic, B. Pitzer, T. Rühr, B. Sankaran, J. Sturm, C. Stachniss, M. Beetz, and W. Burgard. Mobile manipulation of kitchen containers. In Proc. of the IROS'11 Workshop on Results, Challenges and Lessons Learned in Advancing Robots with a Common Platform, San Francisco, CA, USA, 2011. [ bib | .pdf ]
•   R. Kümmerle, G. Grisetti, C. Stachniss, and W. Burgard. Simultaneous parameter calibration, localization, and mapping for robust service robotics. In Proc. of the IEEE Workshop on Advanced Robotics and its Social Impacts, Half-Moon Bay, CA, USA, 2011. [ bib | .pdf ]
•   R. Kümmerle, G. Grisetti, C. Stachniss, and W. Burgard. Simultaneous parameter calibration, localization, and mapping for robust service robotics. In Proc. of the IEEE Workshop on Advanced Robotics and its Social Impacts, Half-Moon Bay, CA, USA, 2011. [ bib | .pdf ]
•   H. Kretzschmar and C. Stachniss. Pose graph compression for laser-based SLAM. In Proc. of the Int. Symposium of Robotics Research (ISRR), Flagstaff, AZ, USA, 2011. Invited presentation. [ bib | .pdf ]
•   H. Kretzschmar, C. Stachniss, and G. Grisetti. Efficient information-theoretic graph pruning for graph-based SLAM with laser range finders. In Proc. of the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), San Francisco, CA, USA, 2011. [ bib | .pdf ]
•   J. Ziegler, H. Kretzschmar, C. Stachniss, G. Grisetti, and W. Burgard. Accurate human motion capture in large areas by combining imu- and laser-based people tracking. In Proc. of the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), San Francisco, CA, USA, 2011. [ bib | .pdf ]
•   B. Frank, C. Stachniss, N. Abdo, and W. Burgard. Efficient motion planning for manipulation robots in environments with deformable objects. In Proc. of the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), San Francisco, CA, USA, 2011. [ bib | .pdf ]
•   B. Frank, C. Stachniss, N. Abdo, and W. Burgard. Using gaussian process regression for efficient motion planning in environments with deformable objects. In Proc. of the AAAI-11 Workshop on Automated Action Planning for Autonomous Mobile Robots (PAMR), San Francisco, CA, USA, 2011. [ bib | .pdf ]
•   D. Maier, M. Bennewitz, and C. Stachniss. Self-supervised obstacle detection for humanoid navigation using monocular vision and sparse laser data. In Proc. of the IEEE International Conference on Robotics & Automation (ICRA), Shanghai, China, 2011. [ bib | .pdf ]
•   B. Steder, M. Ruhnke, S. Grzonka, and W. Burgard. Place recognition in 3D scans using a combination of bag of words and point feature based relative pose estimation. In Proc. of the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2011. [ bib | .pdf ]
•   B. Steder, R. B. Rusu, K. Konolige, and W. Burgard. Point feature extraction on 3D range scans taking into account object boundaries. In Proc. of the IEEE Int. Conf. on Robotics & Automation (ICRA), 2011. [ bib | .pdf ]
•   R. Kümmerle, B. Steder, C. Dornhege, A. Kleiner, G. Grisetti, and W. Burgard. Large scale graph-based SLAM using aerial images as prior information. Journal of Autonomous Robots, 30(1):25-39, 2011. [ bib | DOI | .pdf ]
•   K. Konolige, G. Grisetti, R. Kümmerle, W. Burgard, B. Limketkai, and R. Vincent. Efficient sparse pose adjustment for 2d mapping. In Proc. of the IEEE/RSJ Int. Conf. on Intelligent Robots and Systems (IROS), Taipei, Taiwan, October 2010. [ bib | .pdf ]
•   M. Ruhnke, B. Steder, G. Grisetti, and W Burgard. Unsupervised learning of compact 3d models based on the detection of recurrent structures. In Proc. of the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), Taipei, Taiwan, October 2010. [ bib | .pdf ]
•   Kai M. Wurm, Christian Dornhege, Patrick Eyerich, Cyrill Stachniss, Bernhard Nebel, and Wolfram Burgard. Coordinated exploration with marsupial teams of robots using temporal symbolic planning. In Proc. of the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), Taipei, Taiwan, October 2010. [ bib | .pdf ]
•   Dominik Joho and Wolfram Burgard. Searching for objects: Combining multiple cues to object locations using a maximum entropy model. In Proceedings of the IEEE International Conference on Robotics and Automation (ICRA), pages 723-728, Anchorage, AK, USA, May 2010. [ bib | DOI | .pdf ]
•   J. Müller, C. Gonsior, and W. Burgard. Improved Monte Carlo localization of autonomous robots through simultaneous estimation of motion model parameters. In Proc. of the IEEE International Conference on Robotics & Automation (ICRA), pages 2604-2609, Anchorage, AK, USA, May 2010. [ bib | .pdf ]
•   K.M. Wurm, A. Hornung, M. Bennewitz, C. Stachniss, and W. Burgard. Octomap: A probabilistic, flexible, and compact 3d map representation for robotic systems. In Proc. of the ICRA 2010 Workshop on Best Practice in 3D Perception and Modeling for Mobile Manipulation, Anchorage, USA, May 2010. [ bib | .pdf ]
•   M. Karg, K.M. Wurm, C. Stachniss, K. Dietmayer, and W. Burgard. Consistent mapping of multistory buildings by introducing global constraints to graph-based slam. In Proc. of the IEEE/RSJ International Conference on Robotics & Automation (ICRA), Anchorage, USA, May 2010. [ bib | .pdf ]
•   S. Bouabdallah, C. Bermes, S. Grzonka, C. Gimkiewicz, A. Brenzikofer, R. Hahn, D. Schafroth, G. Grisetti, W. Burgard, and R. Siegwart. Towards palm-size autonomous helicopters. In International Conference and Exhibition on Unmanned Areal Vehicles (UAV), 2010. [ bib ]
•   S. Grzonka, F. Dijoux, A. Karwath, and W. Burgard. Mapping indoor environments based on human activity. In Proc. IEEE International Conference on Robotics and Automation (ICRA), Anchorage, Ak, USA, 2010. [ bib | .pdf ]
•   Boris Lau, Kai O. Arras, and Wolfram Burgard. Multi-model hypothesis group tracking and group size estimation. International Journal of Social Robotics, Springer, 2(1):19-30, 2010. [ bib | http ]
•   Boris Lau, Christoph Sprunk, and Wolfram Burgard. Improved updating of euclidean distance maps and Voronoi diagrams. In Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems, Taipei, Taiwan, 2010. [ bib | .pdf ]
•   M. Cornils, A. Rottmann, and O. Paul. How to extract the sheet resistance and hall mobility from arbitrarily shaped planar four-terminal devices with extended contacts. IEEE Transactions on Electron Devices, 57(9):2087-2097, 2010. [ bib ]
•   A. Rottmann and W. Burgard. Learning non-stationary system dynamics online using Gaussian processes. In Proc. of the German Association for Pattern Recognition (DAGM), pages 192-201, 2010. [ bib ]
•   P. Schopp, A. Rottmann, L. Klingbeil, W. Burgard, and Y. Manoli. Gaussian process based state estimation for a gyroscope-free imu. In Proc.  of the IEEE Sensors Conference, pages 873-878, 2010. [ bib ]
•   G. Grisetti, R. Kümmerle, C. Stachniss, and W. Burgard. A tutorial on graph-based SLAM. IEEE Transactions on Intelligent Transportation Systems Magazine, 2:31-43, 2010. [ bib | .pdf ]
•   W. Burgard, K.M. Wurm, M. Bennewitz, C. Stachniss, A. Hornung, R.B. Rusu, and K. Konolige. Modeling the world around us: An efficient 3d representation for personal robotics. In Workshop on Defining and Solving Realistic Perception Problems in Personal Robotics at the IEEE/RSJ Int. Conf. on Intelligent Robots and Systems, Taipei, Taiwan, 2010. [ bib ]
•   B. Frank, R. Schmedding, C. Stachniss, M. Teschner, and W. Burgard. Learning the elasticity parameters of deformable objects with a manipulation robot. In Proc. of the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), Taipei, Taiwan, 2010. [ bib | .pdf ]
•   A. Hornung, M.Bennewitz, C. Stachniss, H. Strasdat, S. Oßwald, and W. Burgard. Learning adaptive navigation strategies for resource-constrained systems. In Proc. of the Int. Workshop on Evolutionary and Reinforcement Learning for Autonomous Robot Systems, Lisbon, Portugal, 2010. [ bib | .pdf ]
•   J. Sturm, K. Konolige, C. Stachniss, and W. Burgard. 3d pose estimation, tracking and model learning of articulated objects from dense depth video using projected texture stereo. In Proc. of the Workshop RGB-D: Advanced Reasoning with Depth Cameras at Robotics: Science and Systems (RSS), Zaragoza, Spain, 2010. [ bib | .pdf ]
•   B. Frank, R. Schmedding, C. Stachniss, M. Teschner, and W. Burgard. Learning deformable object models for mobile robot path planning using depth cameras and a manipulation robot. In Proc. of the Workshop RGB-D: Advanced Reasoning with Depth Cameras at Robotics: Science and Systems (RSS), Zaragoza, Spain, 2010. [ bib | .pdf ]
•   C. Plagemann, C. Stachniss, J. Hess, F. Endres, and N. Franklin. A nonparametric learning approach to range sensing from omnidirectional vision. Robotics & Autonomous Systems, 58:762-772, 2010. [ bib ]
•   H. Kretzschmar, G. Grisetti, and C. Stachniss. Lifelong map learning for graph-based SLAM in static environments. KI - Künstliche Intelligenz, 24:199-206, 2010. [ bib ]
•   G. Grisetti, R. Kümmerle, C. Stachniss, U. Frese, and C. Hertzberg. Hierarchical optimization on manifolds for online 2d and 3d mapping. In Proc. of the IEEE International Conference on Robotics & Automation (ICRA), Anchorage, Alaska, 2010. [ bib | .pdf ]
•   K.M. Wurm, A. Hornung, M. Bennewitz, C. Stachniss, and W. Burgard. OctoMap: A probabilistic, flexible, and compact 3D map representation for robotic systems. In Proc. of the ICRA 2010 Workshop on Best Practice in 3D Perception and Modeling for Mobile Manipulation, Anchorage, AK, USA, 2010. [ bib | .pdf ]
•   J. Müller, C. Stachniss, K.O. Arras, and W. Burgard. Socially inspired motion planning for mobile robots in populated environments. In Cognitive Systems, Cognitive Systems Monographs. Springer Verlag, 2010. In press. [ bib ]
•   B. Steder, R. B. Rusu, K. Konolige, and W. Burgard. NARF: 3D range image features for object recognition. In Workshop on Defining and Solving Realistic Perception Problems in Personal Robotics at the IEEE/RSJ Int. Conf. on Intelligent Robots and Systems (IROS), Taipei, Taiwan, 2010. [ bib | .pdf ]
•   B. Steder, G. Grisetti, and W. Burgard. Robust place recognition for 3D range data based on point features. In Proc. of the IEEE Int. Conf. on Robotics & Automation (ICRA), 2010. [ bib | .pdf ]
•   J. Sturm, K. Konolige, C. Stachniss, and W. Burgard. Vision-based detection for learning articulation models of cabinet doors and drawers in household environments. In Proc. of the IEEE International Conference on Robotics & Automation (ICRA), Anchorage, Alaska, 2010. [ bib | .pdf ]
•   J. Sturm, K. Konolige, C. Stachniss, and W. Burgard. 3d pose estimation, tracking and model learning of articulated objects from dense depth video using projected texture stereo. In Proceedings of the Workshop on Advanced Reasoning with Depth Cameras at Robotics: Science and Systems Conference (RSS), Zaragoza, Spain, 2010. [ bib ]
•   J. Sturm, A. Jain, C. Stachniss, C. Kemp, and W. Burgard. Operating articulated objects based on experience. In Proc. of the IEEE International Conference on Intelligent Robot Systems (IROS), Taipei, Taiwan, 2010. [ bib | .pdf ]
•   Armin Hornung, Kai M. Wurm, and Maren Bennewitz. Humanoid robot localization in complex indoor environments. In Proc. of the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), Taipei, Taiwan, 2010. [ bib | .pdf ]
•   K.M. Wurm, C. Stachniss, and G. Grisetti. Bridging the gap between feature- and grid-based slam. Robotics & Autonomous Systems, 58(2):140 - 148, 2010. [ bib | DOI ]
•   Boris Lau, Christoph Sprunk, and Wolfram Burgard. Kinodynamic motion planning for mobile robots using splines. In IEEE Intl. Conf. on Intelligent Robots and Systems (IROS), St. Louis, MO, USA, October 2009. [ bib | .pdf ]
•   B. Steder, G. Grisetti, M. Van Loock, and W. Burgard. Robust on-line model-based object detection from range images. In Proc. of the IEEE/RSJ Int. Conf. on Intelligent Robots and Systems (IROS), St. Louis, MO, USA, October 2009. [ bib | .pdf ]
•   K.M. Wurm, R. Kuemmerle, C. Stachniss, and W. Burgard. Improving robot navigation in structured outdoor environments by identifying vegetation from laser data. In Proc. of the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), St. Louis, MO, USA, October 2009. [ bib | .pdf ]
•   Dominik Joho, Martin Senk, and Wolfram Burgard. Learning wayfinding heuristics based on local information of object maps. In Proceedings of the European Conference on Mobile Robots (ECMR), pages 117-122, Mlini/Dubrovnik, Croatia, September 2009. [ bib | .pdf ]
•   R. Kümmerle, B. Steder, C. Dornhege, A. Kleiner, G. Grisetti, and W. Burgard. Large scale graph-based SLAM using aerial images as prior information. In Proceedings of Robotics: Science and Systems (RSS), Seattle, WA, USA, June 2009. [ bib | .pdf ]
•   R. Kümmerle, D. Hähnel, D. Dolgov, S. Thrun, and W. Burgard. Autonomous driving in a multi-level parking structure. In Proc. of the IEEE Int. Conf. on Robotics and Automation (ICRA), pages 3395-3400, Kobe, Japan, May 2009. [ bib | .pdf ]
•   J. Müller, A. Rottmann, L.M. Reindl, and W. Burgard. A probabilistic sonar sensor model for robust localization of a small-size blimp in indoor environments using a particle filter. In Proc. of the IEEE International Conference on Robotics & Automation (ICRA), pages 3589-3594, Kobe, Japan, May 2009. [ bib | .pdf ]
•   A. Hornung, H. Strasdat, M. Bennewitz, and W. Burgard. Learning efficient policies for vision-based navigation. In Proc. of the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2009. [ bib | .pdf ]
•   A. Pretto, E. Menegatti, M. Bennewitz, W. Burgard, and E. Pagello. A visual odometry framework robust to motion blur. In Proc. of the IEEE International Conference on Robotics & Automation (ICRA), 2009. [ bib | .pdf ]
•   S. Grzonka, G. Grisetti, and W. Burgard. Towards a navigation system for autonomous indoor flying. In Proc. IEEE International Conference on Robotics and Automation (ICRA), Kobe, Japan, 2009. [ bib | .pdf ]
•   S. Grzonka, C. Plagemann, G. Grisetti, and W. Burgard. Look-ahead proposals for robust grid-based slam with rao-blackwellized particle filters. In International Journal of Robotics Research (IJRR), pages 191-200, Feb 2009. [ bib | .pdf ]
•   Boris Lau, Kai O. Arras, and Wolfram Burgard. Tracking groups of people with a multi-model hypothesis tracker. In International Conference on Robotics and Automation (ICRA), Kobe, Japan, 2009. [ bib | .pdf ]
•   D. Meyer-Delius, C. Plagemann, and W. Burgard. Probabilistic situation recognition for vehicular traffic scenarios. In Proc. of the IEEE International Conference on Robotics and Automation (ICRA), Kobe, Japan, 2009. [ bib ]
•   Daniel Meyer-Delius, Christian Plagemann, and Wolfram Burgard. Probabilistic situation recognition and its application to vehicular traffic situations. In Proc. of the IEEE Int. Conf. on Robotics & Automation (ICRA), Kobe, Japan, 2009. to appear. [ bib ]
•   Dominik Joho, Christian Plagemann, and Wolfram Burgard. Modeling rfid signal strength and tag detection for localization and mapping. In Proc. of the IEEE Int. Conf. on Robotics & Automation (ICRA), Kobe, Japan, 2009. to appear. [ bib ]
•   A. Rottmann and W. Burgard. Adaptive autonomous control using online value iteration with Gaussian processes. In Proc. of the IEEE Int. Conf. on Robotics & Automation (ICRA), pages 2106-2111, 2009. [ bib ]
•   C. Stachniss. Spatial Modeling and Robot Navigation. Habilitation, University of Freiburg, Department of Computer Science, 2009. [ bib | .pdf ]
•   G. Grisetti, C. Stachniss, and W. Burgard. Non-linear constraint network optimization for efficient map learning. IEEE Transactions on Intelligent Transportation Systems, 10(3):428-439, 2009. [ bib | .pdf ]
•   F. Enders, C. Plagemann, C. Stachniss, and W. Burgard. Scene analysis using latent dirichlet allocation. In Proc. of Robotics: Science and Systems (RSS), Seattle, WA, USA, 2009. [ bib | .pdf ]
•   F. Endres, J. Hess, N. Franklin, C. Plagemann, C. Stachniss, and W. Burgard. Estimating range information from monocular vision. In Workshop Regression in Robotics - Approaches and Applications at Robotics: Science and Systems (RSS), Seattle, WA, USA, 2009. [ bib ]
•   J. Sturm, C. Stachniss, V. Predeap, C. Plagemann, K. Konolige, and W. Burgard. Towards understanding articulated objects. In Workshop Integrating Mobility and Manipulation at Robotics: Science and Systems (RSS), Seattle, WA, USA, 2009. [ bib ]
•   C. Stachniss, C. Plagemann, and A.J. Lilienthal. Gas distribution modeling using sparse gaussian process mixtures. Autonomous Robots, 26:187ff, 2009. [ bib ]
•   C. Stachniss, O. Martinez Mozos, and W. Burgard. Efficient exploration of unknown indoor environments using a team of mobile robots. Annals of Mathematics and Artificial Intelligence, 52:205ff, 2009. [ bib ]
•   C. Stachniss. Robotic Mapping and Exploration, volume 55 of STAR Springer tracts in advanced robotics. Springer, 2009. [ bib ]
•   K.M. Wurm, C. Stachniss, and G. Grisetti. Bridging the gap between feature- and grid-based SLAM. Robotics & Autonomous Systems, 2009. [ bib ]
•   M. Bennewitz, C. Stachniss, S. Behnke, and W. Burgard. Utilizing reflection properties of surfaces to improve mobile robot localization. In Proc. of the IEEE International Conference on Robotics & Automation (ICRA), Kobe, Japan, 2009. [ bib ]
•   H. Strasdat, C. Stachniss, and W. Burgard. Which landmark is useful? learning selection policies for navigation in unknown environments. In Proc. of the IEEE International Conference on Robotics & Automation (ICRA), Kobe, Japan, 2009. [ bib ]
•   B. Frank, C. Stachniss, R. Schmedding, W. Burgard, and M. Teschner. Real-world robot navigation amongst deformable obstacles. In Proc. of the IEEE International Conference on Robotics & Automation (ICRA), Kobe, Japan, 2009. [ bib ]
•   R. Kümmerle, B. Steder, C. Dornhege, M. Ruhnke, G. Grisetti, C. Stachniss, and A. Kleiner. On measuring the accuracy of SLAM algorithms. Journal of Autonomous Robots, 27(4):387-407, 2009. [ bib | DOI | .pdf ]
•   W. Burgard, C. Stachniss, G. Grisetti, B. Steder, R. Kümmerle, C. Dornhege, M. Ruhnke, A. Kleiner, and Juan D. Tardós. A comparison of SLAM algorithms based on a graph of relations. In Proc. of the IEEE/RSJ Int. Conf. on Intelligent Robots and Systems (IROS), St. Louis, MO, USA, 2009. [ bib | .pdf ]
•   M. Ruhnke, B. Steder, G. Grisetti, and W. Burgard. Unsupervised learning of 3D object models from partial views. In Proc. of the IEEE Int. Conf. on Robotics & Automation (ICRA), Kobe, Japan, 2009. [ bib | .pdf ]
•   J. Sturm, C. Stachniss, V. Pradeep, C. Plagemann, K. Konolige, and W. Burgard. Learning kinematic models for articulated objects. In Online Proc. of the Learning Workshop (Snowbird), Clearwater, FL, USA, 2009. [ bib ]
•   C. Eppner, J. Sturm, M. Bennewitz, C. Stachniss, and W. Burgard. Imitation learning with generalized task descriptions. In Proc. of the IEEE International Conference on Robotics & Automation (ICRA), Kobe, Japan, 2009. [ bib | .pdf ]
•   H. Schulz, L. Ott, J. Sturm, and W. Burgard. Learning kinematics from direct self-observation using nearest-neighbor methods. In Proc. of the German Workshop on Robotics, 2009. [ bib | .pdf ]
•   J. Sturm, C. Stachniss, V. Pradeep, C. Plagemann, K. Konolige, and W. Burgard. Towards understanding articulated objects. In Proc. of the Workshop on Robot Manipulation at Robotics: Science and Systems Conference (RSS), 2009. [ bib | .pdf ]
•   J. Sturm, V. Pradeep, C. Stachniss, C. Plagemann, K. Konolige, and W. Burgard. Learning kinematic models for articulated objects. In Proc. of the International Joint Conference on Artificial Intelligence (IJCAI), 2009. [ bib | .pdf ]
•   D. Meyer-Delius, J. Sturm, and W. Burgard. Regression-based online situation recognition for vehicular traffic scenarios. In Proc. of the International Conference on Intelligent Robot Systems (IROS), 2009. [ bib | .pdf ]
•   A. Schneider, J. Sturm, C. Stachniss, M. Reisert, H. Burkhardt, and W. Burgard. Object identification with tactile sensors using bag-of-features. In Proc. of the International Conference on Intelligent Robot Systems (IROS), 2009. [ bib | .pdf ]
•   J. Sturm, C. Plagemann, and W. Burgard. Body schema learning for robotic manipulators from visual self-perception. Journal of Physiology-Paris, 103(3-5):220-231, 2009. Neurorobotics. [ bib | DOI | http ]
•   C. Plagemann. Gaussian Processes for Flexible Robot Learning. PhD thesis, University of Freiburg, Department of Computer Science, December 2008. [ bib ]
•   K.M. Wurm, C. Stachniss, and W. Burgard. Coordinated multi-robot exploration using a segmentation of the environment. In Proc. of the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), Nice, France, September 2008. [ bib | .pdf ]
•   Oscar Martinez Mozos. Semantic Place Labeling with Mobile Robots. PhD thesis, University of Freiburg, Freiburg, Germany, July 2008. [ bib | .pdf ]
•   R. Kümmerle, R. Triebel, P. Pfaff, and W. Burgard. Monte carlo localization in outdoor terrains using multilevel surface maps. Journal of Field Robotics (JFR), 25:346-359, June - July 2008. [ bib | DOI | .pdf ]
•   Hendrik Zender, Oscar Martinez Mozos, Patric Jensfelt, Geert-Jan M. Kruijff, and Wolfram Burgard. Conceptual spatial representations for indoor mobile robots. Robotics and Autonomous Systems, 56(6):493-502, June 2008. [ bib | DOI | .pdf ]
•   M. Luber, K. Arras, C. Plagemann, and W. Burgard. Tracking and classification of dynamic objects: An unsupervised learning approach. In Robotics: Science and Systems (RSS), Zurich, Switzerland, June 2008. [ bib ]
•   J. Sturm, C. Plagemann, and W. Burgard. Adaptive body scheme models for robust robotic manipulation. In Robotics: Science and Systems (RSS), Zurich, Switzerland, June 2008. [ bib ]
•   J. Sturm, C. Plagemann, and W. Burgard. Body scheme learning and life-long adaptation for robotic manipulation. In Proceedings of the Workshop on Robot Manipulation at Robotics: Science and Systems Conference (RSS), Zurich, Switzerland, June 2008. [ bib ]
•   A. Pronobis, O. Martinez Mozos, and B. Caputo. SVM-based discriminative accumulation scheme for place recognition. In Proceedings of the IEEE International Conference on Robotics and Automation, pages 522-529, Pasadena, CA, USA, May 2008. [ bib | .pdf ]
•   W. Burgard, O. Brock, and C. Stachniss, editors. Robotics: Science and Systems III. MIT Press, March 2008. In press. [ bib ]
•   T. Axenbeck, M. Bennewitz, S. Behnke, and W. Burgard. Recognizing complex, parameterized gestures from monocular image sequences. In Proc. of the IEEE-RAS International Conference on Humanoid Robots (Humanoids), 2008. [ bib | .pdf ]
•   M. Bennewitz, T. Axenbeck, S. Behnke, and W. Burgard. Robust recognition of complex gestures for natural human-robot interaction. In Proc. of the Workshop on Interactive Robot Learning at Robotics: Science and Systems Conference (RSS), 2008. [ bib ]
•   S. Grzonka, G. Grisetti, and W. Burgard. Autonomous indoors navigation using a small-size quadrotor. In Workshop Proc. of Intl. Conf. on Simulation, Modeling and Programming for Autonomous Robots (SIMPAR), Venice, Italy, 2008. [ bib | .pdf ]
•   S. Grzonka, S. Bouabdallah, G. Grisetti, W. Burgard, and R. Siegwart. Towards a fully autonomous indoor helicopter. In Workshop of IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), Nice, France, 2008. [ bib | .pdf ]
•   K. Arras, S. Grzonka, M. Luber, and W. Burgard. Efficient people tracking in laser range data using a multi-hypothesis leg-tracker with adaptive occlusion probabilities. In Proc. IEEE International Conference on Robotics and Automation (ICRA), Pasadena, CA, USA, 2008. [ bib | .pdf ]
•   Cyrill Stachniss, Oscar Martinez Mozos, and Wolfram Burgard. Efficient exploration of unknown indoor environments using a team of mobile robots. Annals of Mathematics and Artificial Intelligence, 2008. To appear. [ bib ]
•   R. Triebel, O.M. Mozos, and W. Burgard. Studies in Classification, Data Analysis, and Knowledge Organization, chapter Relational Learning in Mobile Robotics: An Application to Semantic Labeling of Objects in 2D and 3D Environment Maps, pages 293-300. Springer-Verlag, 2008. [ bib | .pdf ]
•   C. Plagemann, K. Kersting, and W. Burgard. Nonstationary gaussian process regression using point estimates of local smoothness. In Proc. of the European Conference on Machine Learning (ECML), Antwerp, Belgium, 2008. [ bib ]
•   W. Burgard, R. Dillmann, C. Plagemann, and N. Vahrenkamp, editors. Proc. of the 10th International Conference on Intelligent Autonomous Systems, Baden-Baden, Germany, July 23-25, 2008. IOS Press, 2008. [ bib ]
•   C. Plagemann, S. Mischke, S. Prentice, K. Kersting, N. Roy, and W. Burgard. Learning predictive terrain models for legged robot locomotion. In Proc. of the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), Nice, France, 2008. [ bib ]
•   U. Reiser, C. Mies, and C. Plagemann. Verteilte software-entwicklung in der robotik - ein integrations- und testframework. In Robotik, Munich, Germany, 2008. In German. [ bib ]
•   P. Pfaff, C. Plagemann, and W. Burgard. Gaussian mixture models for probabilistic localization. In Proc. of the IEEE Int. Conf. on Robotics & Automation (ICRA), Pasadena, CA, USA, 2008. [ bib ]
•   H. Kretzschmar, C. Stachniss, C. Plagemann, and W. Burgard. Estimating landmark locations from geo-referenced photographs. In Proc. of the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), Nice, France, 2008. [ bib | .pdf ]
•   P. Pfaff, C. Stachniss, C. Plagemann, and W. Burgard. Efficiently learning high-dimensional observation models for monte-carlo localization using gaussian mixtures. In Proc. of the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), Nice, France, 2008. [ bib | .pdf ]
•   C. Stachniss, C. Plagemann, A. Lilienthal, and W. Burgard. Gas distribution modeling using sparse gaussian process mixture models. In Proc. of Robotics: Science and Systems (RSS), Zurich, Switzerland, 2008. To appear. [ bib | .pdf ]
•   J. Müller, C. Stachniss, K.O. Arras, and W. Burgard. Socially inspired motion planning for mobile robots in populated environments. In Proceedings of the International Conference on Cognitive Systems (CogSys), Baden Baden, Germany, 2008. [ bib ]
•   C. Stachniss, M. Bennewitz, G. Grisetti, S. Behnke, and W. Burgard. How to learn accurate grid maps with a humanoid. In Proc. of the IEEE International Conference on Robotics & Automation (ICRA), Pasadena, CA, USA, 2008. [ bib | .pdf ]
•   C. Plagemann, F. Endres, J. Hess, C. Stachniss, and W. Burgard. Monocular range sensing: A non-parametric learning approach. In Proc. of the IEEE International Conference on Robotics & Automation (ICRA), Pasadena, CA, USA, 2008. [ bib | .pdf ]
•   G. Grisetti, D. Lordi Rizzini, C. Stachniss, E. Olson, and W. Burgard. Online constraint network optimization for efficient maximum likelihood map learning. In Proc. of the IEEE International Conference on Robotics & Automation (ICRA), Pasadena, CA, USA, 2008. [ bib | .pdf ]
•   B. Frank, M. Becker, C. Stachniss, M. Teschner, and W. Burgard. Efficient path planning for mobile robots in environments with deformable objects. In Proc. of the IEEE International Conference on Robotics & Automation (ICRA), Pasadena, CA, USA, 2008. [ bib | .pdf ]
•   B. Frank, M. Becker, C. Stachniss, M. Teschner, and W. Burgard. Learning cost functions for mobile robot navigation in environments with deformable objects. In Workshop on Path Planning on Cost Maps at the IEEE Int. Conf. on Robotics & Automation (ICRA), Pasadena, CA, USA, 2008. [ bib | .pdf ]
•   B. Steder, G. Grisetti, C. Stachniss, and W. Burgard. Learning visual maps using cameras and inertial sensors. In Workshop on Robotic Perception, International Conference on Computer Vision Theory and Applications, Funchal, Madeira, Portugal, 2008. To appear. [ bib ]
•   B. Steder, G. Grisetti, C. Stachniss, and W. Burgard. Visual SLAM for flying vehicles. IEEE Transactions on Robotics, 24(5):1088-1093, 10 2008. [ bib | .pdf ]
•   B. Steder, G. Grisetti, S. Grzonka, C. Stachniss, and W. Burgard. Estimating consistent elevation maps using down-looking cameras and inertial sensors. In Proc. of the Workshop on Robotic Perception on the International Conference on Computer Vision Theory and Applications, Funchal, Madeira, Portugal, 2008. [ bib | .pdf ]
•   J. Sturm, C. Plagemann, and W. Burgard. Unsupervised body scheme learning through self-perception. In Proc. of the IEEE Int. Conf. on Robotics & Automation (ICRA), pages 3328-3333, Pasadena, CA, USA, 2008. [ bib ]
•   R. Kümmerle, P. Pfaff, R. Triebel, and W. Burgard. Active monte carlo localization in outdoor terrains using multi-level surface maps. In Karsten Berns and Tobias Luksch, editors, Fachgespräch Autonome Mobile Systeme (AMS), pages 22-28, Kaiserslautern, Germany, October 2007. Springer. [ bib | .pdf ]
•   K. Kersting, C. Plagemann, A. Cocora, W. Burgard, and L. De Raedt. Learning to transfer optimal navigation policies. Advanced Robotics. Special Issue on Imitative Robots, 21(9), September 2007. [ bib ]
•   K. M. Wurm, C. Stachniss, G. Grisetti, and W. Burgard. Improved simultaneous localization and mapping using a dual representation of the environment. In Proceedings of the European Conference on Mobile Robots (ECMR), Freiburg, Germany, September 2007. [ bib | .pdf ]
•   S. Grzonka, C. Plagemann, G. Grisetti, and W. Burgard. Look-ahead proposals for robust grid-based slam. In Proc. of the International Conference on Field and Service Robotics (FSR), Chamonix, France, July 2007. [ bib ]
•   Kai M. Wurm. Robustes Lernen von Umgebungskarten durch Integration verschiedener Repräsentationen. Diplomarbeit, Albert-Ludwigs-Universität, Freiburg, July 2007. In German. [ bib | .pdf ]
•   C. Plagemann, K. Kersting, P. Pfaff, and W. Burgard. Gaussian beam processes: A nonparametric bayesian measurement model for range finders. In Robotics: Science and Systems (RSS), Atlanta, Georgia, USA, June 2007. [ bib ]
•   T. Lang, C. Plagemann, and W. Burgard. Adaptive non-stationary kernel regression for terrain modeling. In Robotics: Science and Systems (RSS), Atlanta, Georgia, USA, June 2007. [ bib ]
•   K. Kersting, C. Plagemann, P. Pfaff, and W. Burgard. Most likely heteroscedastic gaussian process regression. In International Conference on Machine Learning (ICML), Corvallis, Oregon, USA, March 2007. [ bib ]
•   C. Plagemann, K. Kersting, P. Pfaff, and W. Burgard. Heteroscedastic gaussian process regression for modeling range sensors in mobile robotics. In Snowbird learning workshop, San Juan, Puerto Rico, March 2007. [ bib ]
•   Dominik Joho. Exploration für mobile Roboter unter Verwendung dreidimensionaler Umgebungsmodelle. Master's thesis, Albert-Ludwigs-Universität Freiburg, 2007. [ bib | .pdf ]
•   R. Kümmerle, R. Triebel, P. Pfaff, and W. Burgard. Monte carlo localization in outdoor terrains using multi-level surface maps. In Proc. of the International Conference on Field and Service Robotics (FSR), Chamonix, France, 2007. [ bib | .pdf ]
•   D. Meyer-Delius and W. Burgard. Maximum-likelihood sample-based maps for mobile robots. In Proc. of the European Conference on Mobile Robots (ECMR), Freiburg, Germany, 2007. [ bib ]
•   D. Meyer-Delius, C. Plagemann, G. von Wichert, W. Feiten, G. Lawitzky, and W. Burgard. A probabilistic relational model for characterizing situations in dynamic multi-agent systems. In In Proc. of the 31th Annual Conference of the German Classification Society on Data Analysis, Machine Learning, and Applications (GFKL), Freiburg, Germany, 2007. [ bib ]
•   Oscar Martinez Mozos, Patric Jensfelt, Hendrik Zender, Geert-Jan M. Kruijff, and Wolfram Burgard. From labels to semantics: An integrated system for conceptual spatial representations of indoor environments for mobile robots. In Proceedings of the IEEE/RSJ IROS 2007 Workshop: Semantic information in robotics, San Diego, CA, USA, 2007. [ bib | .html | .pdf ]
•   Cyrill Stachniss, Giorgio Grisetti, Oscar Martinez Mozos, and Wolfram Burgard. Efficiently learning metric and topological maps with autonomous service robots. it-Information Technology, 49(4):232-237, 2007. [ bib | .pdf ]
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Keywords: collision avoidance, mobile robots, reactive motion control, motion dynamics
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