Vision-based cooperative simultaneous localization and tracking

Localization is one of the most essential capabilities of autonomous robots. Cooperative localization has been proved to be effective in multi-robot localization. However, nearby moving objects could degrade the cooperative localization performance. In this paper, we demonstrate that the cooperative simultaneous localization and tracking approach is superior in challenging scenarios. Localization and moving object tracking are mutually beneficial. The proposed approach is evaluated using humanoid robots in the RoboCup environment in which only uncertain data from onboard cameras and odometry are used. Ample experimental results with ground truthing from laser scanners demonstrate the accuracy and feasibility of the proposed vision-based cooperative simultaneous localization and tracking algorithm.

[1]  Wolfram Burgard,et al.  A Probabilistic Approach to Collaborative Multi-Robot Localization , 2000, Auton. Robots.

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

[3]  Ingemar J. Cox,et al.  Autonomous Robot Vehicles , 1990, Springer New York.

[4]  Sebastian Thrun,et al.  Multi-robot SLAM with Sparse Extended Information Filers , 2003, ISRR.

[5]  Hans-Dieter Burkhard,et al.  Multi Robot Object Tracking and Self Localization Using Visual Percept Relations , 2006, 2006 IEEE/RSJ International Conference on Intelligent Robots and Systems.

[6]  Hugh F. Durrant-Whyte,et al.  Mobile robot localization by tracking geometric beacons , 1991, IEEE Trans. Robotics Autom..

[7]  Bernhard Nebel,et al.  Cooperative sensing in dynamic environments , 2001, Proceedings 2001 IEEE/RSJ International Conference on Intelligent Robots and Systems. Expanding the Societal Role of Robotics in the the Next Millennium (Cat. No.01CH37180).

[8]  Stergios I. Roumeliotis,et al.  Multi-robot SLAM with Unknown Initial Correspondence: The Robot Rendezvous Case , 2006, 2006 IEEE/RSJ International Conference on Intelligent Robots and Systems.

[9]  Michael Beetz,et al.  Cooperative probabilistic state estimation for vision-based autonomous mobile robots , 2002, IEEE Trans. Robotics Autom..

[10]  Stergios I. Roumeliotis,et al.  Distributed multirobot localization , 2002, IEEE Trans. Robotics Autom..

[11]  V. Jilkov,et al.  Survey of maneuvering target tracking. Part V. Multiple-model methods , 2005, IEEE Transactions on Aerospace and Electronic Systems.

[12]  Gaurav S. Sukhatme,et al.  Localization for mobile robot teams using maximum likelihood estimation , 2002, IEEE/RSJ International Conference on Intelligent Robots and Systems.

[13]  A. Rahimi,et al.  Simultaneous localization, calibration, and tracking in an ad hoc sensor network , 2006, 2006 5th International Conference on Information Processing in Sensor Networks.

[14]  Andreas Birk,et al.  Merging Occupancy Grid Maps From Multiple Robots , 2006, Proceedings of the IEEE.

[15]  John J. Leonard,et al.  Cooperative concurrent mapping and localization , 2002, Proceedings 2002 IEEE International Conference on Robotics and Automation (Cat. No.02CH37292).

[16]  W. Burgard,et al.  Markov Localization for Mobile Robots in Dynamic Environments , 1999, J. Artif. Intell. Res..

[17]  Andrew Howard,et al.  Multi-robot Simultaneous Localization and Mapping using Particle Filters , 2005, Int. J. Robotics Res..