Reinforcement Learning-Based Parameter Optimization for Whole-Body Admittance Control with IS-MPC-Reference-Cited by-同舟云学术

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Reinforcement Learning-Based Parameter Optimization for Whole-Body Admittance Control with IS-MPC

Published:2024-01-08 Issue: Volume: Page:1405-1410
ISSN:
Container-title:2024 IEEE/SICE International Symposium on System Integration (SII)
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Author:

Figueroa Nícolas¹,Tafur Julio²,Kheddar Abderrahmane³

Affiliation:

1. University of Montpellier, LIRMM, France and the Pontificia Universidad Católica del Perú,Lima,Perú

2. Pontificia Universidad Católica del Perú,Research, Development and Innovation Laboratory-Engineering Department,Lima,Perú

3. IRL3218, Japan and the CNRS-University of Montpellier, LIRMM, Interactive Digital Human,CNRS-AIST Joint Robotics Laboratory,Montpellier,France

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10417130/10417144/10417367.pdf?arnumber=10417367

Reference16 articles.

1. Stair Climbing Stabilization of the HRP-4 Humanoid Robot using Whole-body Admittance Control

2. Proximal policy optimization algorithms;Schulman;arXiv preprint,2017

3. Learning Task Space Actions for Bipedal Locomotion

4. Quadratic Programming for Multirobot and Task-Space Force Control

5. Mc-Mujoco: Simulating Articulated Robots with FSM Controllers in MuJoCo

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