Bio-inspired Optimization of Fuzzy Logic Controllers for Robotic Autonomous Systems with PSO and ACO

Abstract

In this chapter we describe the application of Ant Colony Optimization (ACO) and Particle Swarm Optimization (PSO) to the optimization of the membership functions’ parameters of a Fuzzy Logic Controller (FLC) in order to find the optimal intelligent controller for an Autonomous Wheeled Mobile Robot. The results obtained by the simulations performed are statistically compared among them and with the results obtained with genetic algorithms in previous work in order to find the best optimization technique for this particular robotics problem.