Behavior analysis of genetic fuzzy controller for an autonomous robot

To program an autonomous robot so that it, acts reliably in a dynamic envir onment is a very hard task. Towards a promising approach to this problem, w e have developed a genetic fuzzy controller for a mobile robot, and showed the possibility by applying it to a simulated robot called Khepera. The rob ot gets input, from eight infrared sensors and operates two motors accordin g to the fuzzy inference based oil the sensory input. This paper attempts t o analyze the adaptive behaviors of the controller by using automata, which indicates the emergence of several strategies to make the robot to navigat e the complex space without bumping against the walls and obstacles.