A cognitive modeling of space using fingerprints of places for mobile robot navigation

In this work we address the problem of perception, spatial cognition and topological navigation for a mobile robot. The objective of this work is to enable the navigation of an autonomous mobile robot (or vehicle) in an indoor (or outdoor) structured environment without relying on maps a priori learned and without using artificial landmarks. A new method for incremental and automatic topological mapping and global localization using fingerprints of places is presented. The fingerprint-based representation permits a reliable, compact and distinctive environment-modeling. Experimental results for mapping indoor and outdoor environments with a mobile robot and a "SMART" vehicle, both equipped with a multi-sensor system composed of two 180deg laser range finders and an omnidirectional camera are also reported

[1]  Roland Siegwart,et al.  Feature extraction and scene interpretation for map-based navigation and map building , 1998, Other Conferences.

[2]  Howie Choset,et al.  Hierarchical simultaneous localization and mapping , 2003, Proceedings 2003 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2003) (Cat. No.03CH37453).

[3]  永福 智志.  The Organization of Learning , 2005, Journal of Cognitive Neuroscience.

[4]  Roland Siegwart,et al.  Topological Global Localization and Mapping with Fingerprints and Uncertainty , 2004, ISER.

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

[6]  José A. Castellanos,et al.  Mobile Robot Localization and Map Building , 1999 .

[7]  David Kortenkamp,et al.  Topological Mapping for Mobile Robots Using a Combination of Sonar and Vision Sensing , 1994, AAAI.

[8]  Leslie Pack Kaelbling,et al.  Acting under uncertainty: discrete Bayesian models for mobile-robot navigation , 1996, Proceedings of IEEE/RSJ International Conference on Intelligent Robots and Systems. IROS '96.

[9]  Keiji Nagatani,et al.  Topological simultaneous localization and mapping (SLAM): toward exact localization without explicit localization , 2001, IEEE Trans. Robotics Autom..

[10]  Roland Siegwart,et al.  Hybrid simultaneous localization and map building: a natural integration of topological and metric , 2003, Robotics Auton. Syst..

[11]  Roland Siegwart,et al.  Environmental modeling with fingerprint sequences for topological global localization , 2003, Proceedings 2003 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2003) (Cat. No.03CH37453).

[12]  Ulrich Nehmzow,et al.  Landmark-based navigation for a mobile robot , 1998 .

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

[14]  Jean-Arcady Meyer,et al.  Landmark-Based Navigation for a Mobile Robot , 1998 .

[15]  Sebastian Thrun,et al.  Learning Metric-Topological Maps for Indoor Mobile Robot Navigation , 1998, Artif. Intell..

[16]  José A. Castellanos,et al.  Mobile Robot Localization and Map Building: A Multisensor Fusion Approach , 2000 .

[17]  E. Tolman.  Cognitive maps in rats and men. , 1948, Psychological review.