Mobile robot control using fuzzy-neural-network for learning human behavior

Authors:
TaeSeok Jin;YoungDae Son;Hideki Hashimoto
Affiliations:
Dept. of Mechatronics Engineering, DongSeo University, Sasang-Gu, Busan, Korea;Dept. of Electronics Engineering, DongSeo University, Sasang-Gu, Busan, Korea;Institute of Industrial Science, the University of Tokyo, Meguro-ku, Tokyo, Japan
Venue:
ICONIP'06 Proceedings of the 13th international conference on Neural information processing - Volume Part III
Year:
2006

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Abstract

The knowledge of human walking behavior has primary importance for mobile agent in order to operate in the human shared space, with minimal disturb of other humans. This paper introduces such an observation and learning framework, which can acquire the human walking behavior from observation of human walking, using CCD cameras of the Intelligent Space. The proposed behavior learning framework applies Fuzzy-Neural Network(FNN) to approximate observed human behavior, with observation data clustering in order to extract important training data from observation. Preliminary experiment and results are shown to demonstrate the merit of the introduced behavior.