Autonomous mobile robot based on behavior decision skill and control skill of the operator

This paper introduces a human skill base control algorithm using artificial neural networks and fuzzy reasoning for an autonomous mobile robot. Neural networks are used to select a suitable motion control pattern in actual environments. The back propagation algorithm adjusts the weights of the neura...

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Bibliographic Details
Published in:Electrical engineering in Japan 2000-04, Vol.131 (2), p.30-39
Main Authors: Yasuno, Takashi, Kamano, Takuya, Suzuki, Takayuki, Uemura, Kazuo, Harada, Hironobu, Kataoka, Yu
Format: Article
Language:English
Subjects:
autonomous mobile robot
fuzzy reasoning
neural networks
operator's skills
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Summary:This paper introduces a human skill base control algorithm using artificial neural networks and fuzzy reasoning for an autonomous mobile robot. Neural networks are used to select a suitable motion control pattern in actual environments. The back propagation algorithm adjusts the weights of the neural networks so that the selected motion control pattern corresponds to the action, which is obtained by the operator's behavior decision skill. To realize the selected motion control pattern, the orientation angle and the speed of the mobile robot are determined by fuzzy reasoning in which fuzzy rules are also automatically tuned so as to simulate the operator's control skill. We have implemented and tested the proposed control algorithm on an autonomous mobile robot and some experimental results demonstrate the effectiveness of the proposed control algorithm for the autonomous mobile robot. © 2000 Scripta Technica, Electr Eng Jpn, 131(2): 30–39, 2000
ISSN:0424-7760
1520-6416
DOI:10.1002/(SICI)1520-6416(20000430)131:2<30::AID-EEJ4>3.0.CO;2-4