Control of autonomous robots using genetic algorithms and neural networks

Abstract

A simulator of autonomous robots in a non-structured environment is presented. This simulator is used to develop alternative programming techniques for robot control. These techniques consist basically of using genetic algorithms to train neural networks that are used to control the autonomous robots. The robots' autonomous control is presented and the computational aspects are discussed.