Model-free reinforcement learning for robust locomotion using demonstrations from trajectory optimization

Model-free reinforcement learning for robust locomotion using demonstrations from trajectory optimization

We present a general, two-stage reinforcement learning approach to create robust policies that can be deployed on real robots without any additional training using a single demonstration generated by trajectory optimization. The demonstration is used in the first stage as a starting point to facilit...

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Bibliographic Details
Main Authors: Miroslav Bogdanovic, Majid Khadiv , Ludovic Righetti 
Format: Article
Language:English
Published: Frontiers Media S.A. 2022-08-01
Series:Frontiers in Robotics and AI
Subjects:
legged locomotion
deep reinforcement learning
trajectory optimization
robust control policies
contact uncertainty
Online Access:https://www.frontiersin.org/articles/10.3389/frobt.2022.854212/full

Internet

https://www.frontiersin.org/articles/10.3389/frobt.2022.854212/full

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