Joint self-localization and tracking of generic objects in 3D range data

Both, the estimation of the trajectory of a sensor and the detection and tracking of moving objects are essential tasks for autonomous robots. This work proposes a new algorithm that treats both problems jointly. The sole input is a sequence of dense 3D measurements as returned by multi-layer laser scanners or time-of-flight cameras. A major characteristic of the proposed approach is its applicability to any type of environment since specific object models are not used at any algorithm stage. More specifically, precise localization in non-flat environments is possible as well as the detection and tracking of e.g. trams or recumbent bicycles. Moreover, 3D shape estimation of moving objects is inherent to the proposed method. Thorough evaluation is conducted on a vehicular platform with a mounted Velodyne HDL-64E laser scanner.

[1]  Rüdiger Dillmann,et al.  Obstacle detection with a Photonic Mixing Device-camera in autonomous vehicles , 2008, Int. J. Intell. Syst. Technol. Appl..

[2]  Wolfram Burgard,et al.  Probabilistic Robotics (Intelligent Robotics and Autonomous Agents) , 2005 .

[3]  Gérard G. Medioni,et al.  Object modeling by registration of multiple range images , 1991, Proceedings. 1991 IEEE International Conference on Robotics and Automation.

[4]  G. Wanielik,et al.  Obstacle Detection and Pedestrian Recognition Using A 3D PMD Camera , 2006, 2006 IEEE Intelligent Vehicles Symposium.

[5]  Y. Bar-Shalom.  Tracking and data association , 1988 .

[6]  Rüdiger Dillmann,et al.  Recursive importance sampling for efficient grid-based occupancy filtering in dynamic environments , 2010, 2010 IEEE International Conference on Robotics and Automation.

[7]  Trung-Dung Vu,et al.  Grid-based localization and online mapping with moving objects detection and tracking: new results , 2008, 2008 IEEE Intelligent Vehicles Symposium.

[8]  Oleg V. Michailovich,et al.  Segmentation of Tracking Sequences Using Dynamically Updated Adaptive Learning , 2008, IEEE Transactions on Image Processing.

[9]  Paul Newman,et al.  High quality 3D laser ranging under general vehicle motion , 2008, 2008 IEEE International Conference on Robotics and Automation.

[10]  Samuel J. Davey,et al.  A Comparison of Detection Performance for Several Track-before-Detect Algorithms , 2008, 2008 11th International Conference on Information Fusion.

[11]  F. Nashashibi,et al.  Laser-based vehicles tracking and classification using occlusion reasoning and confidence estimation , 2008, 2008 IEEE Intelligent Vehicles Symposium.

[12]  Joachim Hertzberg,et al.  6D SLAM—3D mapping outdoor environments , 2007, J. Field Robotics.

[13]  Paul J. Besl,et al.  A Method for Registration of 3-D Shapes , 1992, IEEE Trans. Pattern Anal. Mach. Intell..

[14]  Thierry Fraichard,et al.  Motion estimation from range images in dynamic outdoor scenes , 2010, 2010 IEEE International Conference on Robotics and Automation.

[15]  G. Gate,et al.  Using targets appearance to improve pedestrian classification with a laser scanner , 2008, 2008 IEEE Intelligent Vehicles Symposium.

[16]  Tim Bailey,et al.  Scan segments matching for pairwise 3D alignment , 2012, 2012 IEEE International Conference on Robotics and Automation.

[17]  Klaus C. J. Dietmayer,et al.  Fuzzy estimation and segmentation for laser range scans , 2009, 2009 12th International Conference on Information Fusion.

[18]  Sebastian Thrun,et al.  Model based vehicle detection and tracking for autonomous urban driving , 2009, Auton. Robots.

[19]  Christoph Stiller,et al.  Segmentation of 3D lidar data in non-flat urban environments using a local convexity criterion , 2009, 2009 IEEE Intelligent Vehicles Symposium.

[20]  Michael Bosse,et al.  Continuous 3D scan-matching with a spinning 2D laser , 2009, 2009 IEEE International Conference on Robotics and Automation.

[21]  Uwe Franke,et al.  Efficient representation of traffic scenes by means of dynamic stixels , 2010, 2010 IEEE Intelligent Vehicles Symposium.

[22]  Joachim Hertzberg,et al.  Evolving interface design for robot search tasks: Research Articles , 2007 .

[23]  Andrea Censi,et al.  On achievable accuracy for range-finder localization , 2007, Proceedings 2007 IEEE International Conference on Robotics and Automation.

[24]  Hugh F. Durrant-Whyte,et al.  Simultaneous Localization, Mapping and Moving Object Tracking , 2007, Int. J. Robotics Res..

[25]  Fabio Tozeto Ramos,et al.  An integrated probabilistic model for scan-matching, moving object detection and motion estimation , 2010, 2010 IEEE International Conference on Robotics and Automation.

[26]  Julius Ziegler,et al.  Team AnnieWAY's autonomous system for the 2007 DARPA Urban Challenge , 2008, J. Field Robotics.

[27]  Christoph Stiller,et al.  Velodyne SLAM , 2011, 2011 IEEE Intelligent Vehicles Symposium (IV).