Abstract
This paper proposes computational intelligence for a perceptual system of a partner robot. The robot requires the capability of visual perception to interact with a human. Basically, a robot should perform moving object extraction, clustering, and classification for visual perception used in the interaction with human. In this paper, we propose a total system for human clustering for a partner robot by using long-term memory, k-means, self-organizing map and fuzzy controller is used for the motion output. The experimental results show that the partner robot can perform the human clustering.
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Sulistijono, I.A., Kubota, N. (2005). Human Clustering for a Partner Robot Based on Computational Intelligence. In: Wang, L., Jin, Y. (eds) Fuzzy Systems and Knowledge Discovery. FSKD 2005. Lecture Notes in Computer Science(), vol 3613. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11539506_124
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DOI: https://doi.org/10.1007/11539506_124
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-28312-6
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