Mobile Robot Simultaneous Localization and Mapping in Dynamic Environments

We propose an on-line algorithm for simultaneous localization and mapping of dynamic environments. Our algorithm is capable of differentiating static and dynamic parts of the environment and representing them appropriately on the map. Our approach is based on maintaining two occupancy grids. One grid models the static parts of the environment, and the other models the dynamic parts of the environment. The union of the two grid maps provides a complete description of the environment over time. We also maintain a third map containing information about static landmarks detected in the environment. These landmarks provide the robot with localization. Results in simulation and real robots experiments show the efficiency of our approach and also show how the differentiation of dynamic and static entities in the environment and SLAM can be mutually beneficial.

[1]  Charles E. Thorpe,et al.  Simultaneous localization and mapping with detection and tracking of moving objects , 2002, Proceedings 2002 IEEE International Conference on Robotics and Automation (Cat. No.02CH37292).

[2]  Evangelos E. Milios,et al.  Globally Consistent Range Scan Alignment for Environment Mapping , 1997, Auton. Robots.

[3]  Sebastian Thrun,et al.  A probabilistic technique for simultaneous localization and door state estimation with mobile robots in dynamic environments , 2002, IEEE/RSJ International Conference on Intelligent Robots and Systems.

[4]  Sebastian Thrun,et al.  Online simultaneous localization and mapping with detection and tracking of moving objects: theory and results from a ground vehicle in crowded urban areas , 2003, 2003 IEEE International Conference on Robotics and Automation (Cat. No.03CH37422).

[5]  Gaurav S. Sukhatme,et al.  Online simultaneous localization and mapping in dynamic environments , 2004, IEEE International Conference on Robotics and Automation, 2004. Proceedings. ICRA '04. 2004.

[6]  Gaurav S. Sukhatme,et al.  Towards Mapping Dynamic Environments , 2003 .

[7]  Wolfram Burgard,et al.  A real-time algorithm for mobile robot mapping with applications to multi-robot and 3D mapping , 2000, Proceedings 2000 ICRA. Millennium Conference. IEEE International Conference on Robotics and Automation. Symposia Proceedings (Cat. No.00CH37065).

[8]  John J. Leonard,et al.  Explore and return: experimental validation of real-time concurrent mapping and localization , 2002, Proceedings 2002 IEEE International Conference on Robotics and Automation (Cat. No.02CH37292).

[9]  Sebastian Thrun,et al.  FastSLAM: a factored solution to the simultaneous localization and mapping problem , 2002, AAAI/IAAI.

[10]  José A. Castellanos,et al.  Multisensor fusion for simultaneous localization and map building , 2001, IEEE Trans. Robotics Autom..

[11]  Wolfram Burgard,et al.  A Probabilistic Approach to Concurrent Mapping and Localization for Mobile Robots , 1998, Auton. Robots.

[12]  Juan Andrade-Cetto,et al.  Concurrent Map Building and Localization on Indoor Dynamic Environments , 2002, Int. J. Pattern Recognit. Artif. Intell..

[13]  François Charpillet,et al.  Mobile robot localization in dynamic environments using places recognition , 1998, Proceedings. 1998 IEEE International Conference on Robotics and Automation (Cat. No.98CH36146).

[14]  Wolfram Burgard,et al.  Map building with mobile robots in dynamic environments , 2003, 2003 IEEE International Conference on Robotics and Automation (Cat. No.03CH37422).

[15]  J. W. Fenwick,et al.  Collaborative concurrent mapping and localization , 2001 .

[16]  Hugh F. Durrant-Whyte,et al.  A solution to the simultaneous localization and map building (SLAM) problem , 2001, IEEE Trans. Robotics Autom..

[17]  Viii Supervisor.  Sonar-Based Real-World Mapping and Navigation , 2001 .

[18]  Sebastian Thrun,et al.  Robotic mapping: a survey , 2003 .

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

[20]  Gaurav S. Sukhatme,et al.  Most valuable player: a robot device server for distributed control , 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).

[21]  John J. Leonard,et al.  Robust Mapping and Localization in Indoor Environments Using Sonar Data , 2002, Int. J. Robotics Res..

[22]  Sebastian Thrun,et al.  Results for outdoor-SLAM using sparse extended information filters , 2003, 2003 IEEE International Conference on Robotics and Automation (Cat. No.03CH37422).

[23]  Wolfram Burgard,et al.  Map building with mobile robots in populated environments , 2002, IEEE/RSJ International Conference on Intelligent Robots and Systems.

[24]  Alberto Elfes,et al.  Using occupancy grids for mobile robot perception and navigation , 1989, Computer.

[25]  Eduardo Mario Nebot,et al.  Improving computational and memory requirements of simultaneous localization and map building algorithms , 2002, Proceedings 2002 IEEE International Conference on Robotics and Automation (Cat. No.02CH37292).

[26]  Wolfram Burgard,et al.  An efficient fastSLAM algorithm for generating maps of large-scale cyclic environments from raw laser range measurements , 2003, Proceedings 2003 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2003) (Cat. No.03CH37453).

[27]  Scott Sanner,et al.  Towards object mapping in non-stationary environments with mobile robots , 2002, IEEE/RSJ International Conference on Intelligent Robots and Systems.

[28]  Eduardo Mario Nebot,et al.  Real time data association for FastSLAM , 2003, 2003 IEEE International Conference on Robotics and Automation (Cat. No.03CH37422).

[29]  Eduardo Mario Nebot,et al.  Optimization of the simultaneous localization and map-building algorithm for real-time implementation , 2001, IEEE Trans. Robotics Autom..

[30]  Hans P. Moravec.  Sensor Fusion in Certainty Grids for Mobile Robots , 1988, AI Mag..