A novel approach to locomotion learning: Actor-Critic architecture using central pattern generators and dynamic motor primitives.

ABSTRACT: In this article, we propose an architecture of a bio-inspired controller that addresses the problem of learning different locomotion gaits for different robot morphologies. The modeling objective is split into two: baseline motion modeling and dynamics adaptation. Baseline motion modeling aims to achieve fundamental functions of a certain type of locomotion and dynamics adaptation provides a "reshaping" function for adapting the baseline motion to desired motion. Based on this assumption, a three-layer architecture is developed using central pattern generators (CPGs, a bio-inspired locomotor center for the baseline motion) and dynamic motor primitives (DMPs, a model with universal "reshaping" functions). In this article, we use this architecture with the actor-critic algorithms for finding

SUBMITTER: Li C 

PROVIDER: S-EPMC4183130 | biostudies-literature | 2014

REPOSITORIES: biostudies-literature