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Behavior Fusion of Robot Navigation Using a Fuzzy Neural Network

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2 Author(s)
Kai-Tai Song ; Department of Electrical and Control Engineering, National Chiao rung University, Hsinchu, Taiwan R.O.C. e-mail:, ; Jean-Yuan Lin

This paper presents a design of behavior-fusion architecture for mobile robot navigation. We first design three behaviors for robot navigation, including obstacle avoidance, wall following, and goal seeking. We implement these primitive behaviors by using fuzzy-logic control approaches. Then, the fusion weight of each behavior is determined by using the proposed behavior-fusion neural network. The neural network maps the current environment sensor data to suitable fusion weights. Both computer simulation and practical experiments verify the effectiveness of the method.

Published in:

2006 IEEE International Conference on Systems, Man and Cybernetics  (Volume:6 )

Date of Conference:

8-11 Oct. 2006