Skip to Main Content
Recently, biologically inspired approaches have received much attention for robot control. A typical example of them is control of rhythmic behaviors by Central Pattern Generator (CPG). However, this control has a problem that there are few theories to determine parameters of CPG. For this reason, they are determined experimentally. In this paper, we propose a combination method of Genetic Algorithm and Reinforcement Learning for determining parameters of CPG, and apply to a quadruped robot with the CPG controller. Simulation results show that the robot obtains walking behaviors automatically through learning process without using the parameters set by knowledge of designers.
Date of Conference: 18-23 July 2010