Legged Robots that Keep on Learning: Fine-Tuning Locomotion Policies in the Real World

Author:

Smith Laura1,Kew J. Chase2,Bin Peng Xue1,Ha Sehoon2,Tan Jie2,Levine Sergey1

Affiliation:

1. Berkeley AI Research, UC Berkeley

2. Google Research

Funder

Office of Naval Research

Google

NSF

Publisher

IEEE

Reference43 articles.

1. Mode-adaptive neural networks for quadruped motion control

2. Learning to walk in the real world with minimal human effort;ha;ArXiv,2020

3. Efficient adaptation for end-to-end vision-based robotic manipulation;julian;ArXiv,2020

4. Learning Fast Adaptation With Meta Strategy Optimization

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