Appearance-based place recognition for topological localization

This paper presents a new appearance-based place recognition system for topological localization. The method uses a panoramic vision system to sense the environment. Color images are classified in real-time based on nearest-neighbor learning, image histogram matching, and a simple voting scheme. The system has been evaluated with eight cross-sequence tests in four unmodified environments, three indoors and one outdoors. In all eight cases, the system successfully tracked the mobile robot's position. The system correctly classified between 87% and 98% of the input color images. For the remaining images, the system was either momentarily confused or uncertain, but never classified an image incorrectly.

[1]  Henrik I. Christensen,et al.  Laser based pose tracking , 1999, Proceedings 1999 IEEE International Conference on Robotics and Automation (Cat. No.99CH36288C).

[2]  J. M. M. Montiel,et al.  Continuous mobile robot localization: vision vs. laser , 1999, Proceedings 1999 IEEE International Conference on Robotics and Automation (Cat. No.99CH36288C).

[3]  Michael J. Swain,et al.  Navigation for Everyday Life , 1996, AAAI/IAAI, Vol. 2.

[4]  Anil K. Jain,et al.  Mobile robot localization via classification of multisensor maps , 1994, Proceedings of the 1994 IEEE International Conference on Robotics and Automation.

[5]  Illah R. Nourbakhsh,et al.  Topological robot localization by training a vision-based transition detector , 1999, Proceedings 1999 IEEE/RSJ International Conference on Intelligent Robots and Systems. Human and Environment Friendly Robots with High Intelligence and Emotional Quotients (Cat. No.99CH36289).

[6]  Fumihito Arai,et al.  Vision based navigation system for autonomous mobile robot with global matching , 1999, Proceedings 1999 IEEE International Conference on Robotics and Automation (Cat. No.99CH36288C).

[7]  Illah R. Nourbakhsh,et al.  Automatic Mapping of Dynamic Office Environments , 1999, Auton. Robots.

[8]  Don Ray Murray,et al.  Cooperative robot localization with vision-based mapping , 1999, Proceedings 1999 IEEE International Conference on Robotics and Automation (Cat. No.99CH36288C).

[9]  Martial Hebert,et al.  Evaluation of Image-Based Landmark Recognition Techniques , 1998 .

[10]  Benjamin Kuipers,et al.  A robot exploration and mapping strategy based on a semantic hierarchy of spatial representations , 1991, Robotics Auton. Syst..

[11]  David Kortenkamp,et al.  Using Gateways To Build A Route Map , 1992, Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems.

[12]  Maja J. Mataric,et al.  Integration of representation into goal-driven behavior-based robots , 1992, IEEE Trans. Robotics Autom..

[13]  Benjamin Kuipers,et al.  Modeling Spatial Knowledge , 1978, IJCAI.

[14]  Nicola Tomatis,et al.  Improving robustness and precision in mobile robot localization by using laser range finding and monocular vision , 1999, 1999 Third European Workshop on Advanced Mobile Robots (Eurobot'99). Proceedings (Cat. No.99EX355).

[15]  David J. Kriegman,et al.  Vision-based motion planning and exploration algorithms for mobile robots , 1995, IEEE Trans. Robotics Autom..

[16]  Luis Montano,et al.  Goal directed reactive robot navigation with relocation using laser and vision , 1999, Proceedings 1999 IEEE International Conference on Robotics and Automation (Cat. No.99CH36288C).

[17]  Sethuraman Panchanathan,et al.  Review of Image and Video Indexing Techniques , 1997, J. Vis. Commun. Image Represent..

[18]  Carlo Tomasi,et al.  The Earth Mover’s Distance , 2001 .

[19]  Sebastian Thrun.  Finding landmarks for mobile robot navigation , 1998, Proceedings. 1998 IEEE International Conference on Robotics and Automation (Cat. No.98CH36146).

[20]  Shree K. Nayar,et al.  Catadioptric omnidirectional camera , 1997, Proceedings of IEEE Computer Society Conference on Computer Vision and Pattern Recognition.