Designing a Control System for an Autonomous Robot Using an Evolutionary Algorithm

Abstract

AbstractHand-design of control systems for autonomous robots that act in dynamic or noisy environments is a complex task.In this paper, a new technique for controller design, termed decisionvector, is presented. An evolutionary approach is proposed: the control systems (candidate solutions) are made up of the set of robot states with respect to the obstacles it can detect, and the corresponding actions to take on each one of those situations.This initial work carries out the evolution of controllers in two environments, so that it is clear that, in spite of the simplicity of the proposed model, it is powerful enough to guide the robot to reach a target avoiding obstacles, and even, tracking a spread mark on the ground.KeywordsGood IndividualSensor ActivationNoisy EnvironmentAutonomous RobotReal RobotThese keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.