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Stability Control of Biped Robot on Static and Dynamic Platforms Based on Hybrid Reinforcement Learning

thesis
posted on 09.12.2020, 23:46 by AO XI
In this work, we proposed a novel Hybrid Reinforcement Learning algorithm that incorporates the model-based reinforcement learning scheme with the model-free reinforcement learning framework, where the sample efficiency was improved while still retaining the desired control performance. The proposed learning framework was successfully applied to a complex biped robot model, where the robot was able to maintain balance on a rotating platform. Experiment results also showed that the proposed algorithm was able to generate stable walking gaits for the robot to walk on both static and dynamic platforms without falling down.

History

Campus location

Australia

Principal supervisor

Chao Chen

Additional supervisor 1

Dacheng Tao

Year of Award

2020

Department, School or Centre

Mechanical and Aerospace Engineering

Course

Doctor of Philosophy

Degree Type

DOCTORATE

Exports