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.
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Jin, T., Son, Y., Hashimoto, H. (2006). Mobile Robot Control Using Fuzzy-Neural-Network for Learning Human Behavior. In: King, I., Wang, J., Chan, LW., Wang, D. (eds) Neural Information Processing. ICONIP 2006. Lecture Notes in Computer Science, vol 4234. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11893295_96
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DOI: https://doi.org/10.1007/11893295_96
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