Evolutionary Computation for Simultaneous Localization and Mapping Based on Topological Map of a Mobile Robot

  • Authors:

  • Hironobu Sasaki;Naoyuki Kubota;Kazuhiko Taniguchi

  • Affiliations:

  • Department of System Design, Tokyo Metropolitan University, Tokyo, Japan 191-0065;Department of System Design, Tokyo Metropolitan University, Tokyo, Japan 191-0065;Kyoto R and D Center, Kinden Corp., Japan

  • Venue:
  • ICIRA '08 Proceedings of the First International Conference on Intelligent Robotics and Applications: Part I
  • Year:
  • 2008

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Abstract

This paper proposes a method for simultaneous localization and mapping based on evolutionary computation. First, we propose a map building method based on growing topological neural networks. According to the measured distance by laser range finder, the map is updated sequentially. If the difference between the measured distance and its corresponding map data is large, the robot updates the self-location by using evolution strategy. Next, we propose a refining method of the topological map. Finally, we discuss the effectiveness of the proposed methods through several experimental results and comparison results.