Optimization of fuzzy controllers for autonomous mobile robots using the grey wolf optimizer

Abstract

Through the advancement of science and technology, every day new methods or computational techniques are emerging that allow to solve problems in widely different areas, such as medicine, engineering, even in any industrial process. Optimization is of vital importance in applications and in industry, the main objective being to find the best possible solution to a particular problem of interest. In this work we propose to use the Grey Wolf Optimizer (GWO), which is a relatively new meta-heuristic, inspired by the hunting behavior and leadership hierarchy of grey wolves, for the optimization of fuzzy controllers for mobile autonomous robots. In addition to analyzing and explaining the proposed methodology based on GWO we are presenting simulation results for a two wheeled autonomous mobile robot to validate the efficiency of the proposed approach.