Experimental investigation of a prediction algorithm for an indoor SLAM platform

  • Authors:
  • Jung-Fu Hou;Yu-Shin Chou;Yau-Zen Chang;Jing-Sin Liu

  • Affiliations:
  • Department of Mechanical Engineering, Chung-Gung University, Taiwan;Institute of Information Science, Academia Sinica, Taiwan;Department of Mechanical Engineering, Chung-Gung University, Taiwan;Institute of Information Science, Academia Sinica, Taiwan

  • Venue:
  • ICIRA'10 Proceedings of the Third international conference on Intelligent robotics and applications - Volume Part II
  • Year:
  • 2010

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Abstract

This paper presents a scheme for the indoor simultaneous localization and mapping (SLAM) problem. The scheme is based on the scan matching method and is treated as an optimization problem solve by the Simplex method. The two-dimensional distance transform method is used to facilitate the cost value evaluation. In order to register scanned maps with built map through maximum overlap between the maps, a predictive algorithm is proposed. The algorithm can not only reduce search scope but also discard unexpected objects that may cause false match. The approach is investigated by an experimental platform with differential drives. The ICP-SLAM is also implemented for performance comparison. Experimental result shows that the prediction algorithm can improve accumulation error in the indoor environment.