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Neural network and fuzzy logic techniques based collision avoidance for a mobile robot

Published online by Cambridge University Press:  01 November 1997

Minglu Zhang ,
Shangxian Peng  and
Qinghao Meng
Minglu Zhang
Affiliation:
Department of Mechanical Engineering, Hebei University of Technology, Tian Jin City, P.R. of China, 300130
Shangxian Peng
Affiliation:
Intelligent Machine Institute, Tian Jin University, Tian Jin City, P.R. of China, 300072
Qinghao Meng
Affiliation:
Department of Mechanical Engineering, Hebei University of Technology, Tian Jin City, P.R. of China, 300130
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Abstract

This paper is concerned with a mobile robot reactive navigation in an unknown cluttered environment based on neural network and fuzzy logic. Reactive navigation is a mapping between sensory data and commands without planning. This article's task is to provide a steering command letting a mobile robot avoid a collision with obstacles. In this paper, the authors explain how to perform a currently perceptual space partitioning for a mobile robot by the use of an ART neural network, and then, how to build a 3-dimensional fuzzy controller for mobile robot reactive navigation. The results presented, whether experimented or simulation, show that our method is well adapted to this type of problem.

Keywords

Mobile robotObstacle avoidanceNeural networksFuzzy logic
Type
Research Article
Information
Robotica , Volume 15 , Issue 6 , November 1997 , pp. 627 - 632
Copyright
© 1997 Cambridge University Press

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