Obstacle avoidance of mobile robot using fuzzy behaviour-based control with module learning

Abstract

Intelligent control is being widely studied in the field of robotics. A construction method of an intelligent control system is the fuzzy behavior-based control which decomposes a task into each elemental behavior like a subsumption architecture, and each elemental behavior is realized by fuzzy reasoning. In the paper, a module learning method is proposed for such a system, because the robot will be able to get more general knowledge or fuzzy reasoning than a central learning method. In particular, the module learning method is applied to an obstacle avoidance problem of a mobile robot. The effectiveness of the present method is illustrated through some simulations.