Abstract
The principal aim of this study is to show how an autonomous mobile robot can acquire the optimal action to avoid moving multiobstacles through the interaction with the real world. In this paper, we propose a new architecture using the hierarchical fuzzy rules, fuzzy performance evaluation system and learning automata. By using our proposed method, the robot acquires the fine behavior to move to the goal, avoiding moving obstacles, simultaneously by using the steering and velocity control inputs. Also we show the experimental results to confirm the feasibility of our method.
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© 1996 Springer-Verlag Berlin Heidelberg
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Aoki, T., Oka, T., Hayakawa, S., Suzuki, T., Okuma, S. (1996). Experimental study on acquisition of optimal action for autonomous mobile robot to avoid moving multiobstacles. In: Furuhashi, T., Uchikawa, Y. (eds) Fuzzy Logic, Neural Networks, and Evolutionary Computation. WWW 1995. Lecture Notes in Computer Science, vol 1152. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-61988-7_18
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DOI: https://doi.org/10.1007/3-540-61988-7_18
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