Perception-based genetic algorithm for a mobile robot with fuzzy controllers

The paper deals with a genetic algorithm for acquiring adaptive behaviors of a fuzzy based mobile robot. If its environmental state is stable or fixed, the behaviors of the robot can be optimized by conventional genetic algorithms. Otherwise, the behavior should be tuned by adaptation and learning according to the change of its environment. However, it is difficult for the robot to maintain behaviors suitable to various environmental states in the dynamic environment. Therefore, the paper proposes a genetic algorithm based on the perceived information about the dynamic environment, which is called a perception based genetic algorithm. We apply the proposed method to collision avoidance behaviors of the mobile robot in a dynamic environment. Furthermore, we conduct several computer simulations. Simulation results show that the proposed method can maintain various behaviors according to environmental changes