Knowledge insertion in evolved fuzzy controllers

A fuzzy controller is usually designed by formulating the knowledge of a human expert into a set of linguistic variables and fuzzy rules. One of the most successful methods to automate the fuzzy controllers development process are evolutionary algorithms. In this work, we study apriori knowledge insertion into fuzzy systems implemented with the Fuzzy Voronoi representation. The proposed strategy is evaluated on an obstacle avoidance problem with a simulated mobile robot.