Reinforcement Learning for Biped Locomotion

Abstract

This paper studies the reinforcement learning (RL) method for central pattern generators (CPG) that generates stable rhythmic movements such as biped locomotion. RL for biped locomotion is very difficult, since the biped robot is highly unstable and the system has continuous state and action spaces with a high degree of freedom. In order to deal with RL for CPG, we propose a new RL method called the CPG-actor-critic method. We applied this method to the RL for the biped robot. The computer simulation showed that our RL method was able to train the CPG such that the biped robot walk stably.