Evolution of a P/N fuzzy obstacle avoidance controller for an autonomous robot

A fuzzy controller is designed for an autonomous robot. The controller is given the capability for obstacle avoidance by using negative fuzzy rules in conjunction with traditional positive ones. Negative fuzzy rules prescribe actions to be avoided rather than performed. A rule base of positive rules is specified by an expert for directing the robot to the target in the absence of obstacles, while a rule base of negative rules is experimentally determined from operation of the robot in the presence of obstacles. The consequents of the negative-rule system are codified into a chromosome, and this chromosome is evolved using an evolutionary algorithm. The resulting PIN fuzzy system has far fewer rules than would be necessary for an obstacle avoidance controller using purely positive rules, while in addition retaining greater interpretability.