Monte Carlo SLAM method for a small mobile robot with short-range sensors

Authors:
Kohei Yamada;Yohei Nakada;Takashi Matsumoto
Affiliations:
Waseda University, Tokyo, Japan;Waseda University, Tokyo, Japan;Waseda University, Tokyo, Japan
Venue:
MIC '08 Proceedings of the 27th IASTED International Conference on Modelling, Identification and Control
Year:
2008

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Abstract

We propose a novel extension of the grid-based Monte Carlo SLAM approach for a small mobile robot with short-range distance sensors. The proposed approach considers probabilistic hidden variables in the model, instead of the noisy local maps generated in deterministic conversion processes. These hidden variables reduce the effect of unwanted sensor noise in the mapping processes. To evaluate the proposed approach, it is tested against a numerical experiment based on a simulator of a small mobile robot, Khepella II, with various sensor noise levels.