Reactive Stepping for Humanoid Robots using Reinforcement Learning: Application to Standing Push Recovery on the Exoskeleton Atalante-Reference-Cited by-同舟云学术

Reactive Stepping for Humanoid Robots using Reinforcement Learning: Application to Standing Push Recovery on the Exoskeleton Atalante

Published:2022-10-23 Issue: Volume: Page:
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Container-title:2022 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)
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Author:

Duburcq Alexis¹,Schramm Fabian¹,Boeris Guilhem¹,Bredeche Nicolas²,Chevaleyre Yann³

Affiliation:

1. Wandercraft,Paris,France

2. Sorbonne Université, CNRS, Institut des Systèmes Intelligents et de Robotique, ISIR,Paris,France,F-75005

3. Université Paris-Dauphine, PSL, CNRS, Laboratoire d'analyse et modélisation de systèmes pour l,Paris,France

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/9981026/9981028/09982234.pdf?arnumber=9982234

Reference41 articles.

1. Decoding Motor Skills of Artificial Intelligence and Human Policies: A Study on Humanoid and Human Balance Control

2. Push Recovery Strategies through Deep Reinforcement Learning

3. High-dimensional continuous control using generalized advantage estimation;schulman;International Conference on Learning Representations (ICLR),2016

4. Dynamic Balance Force Control for compliant humanoid robots

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