OSCAR: Data-Driven Operational Space Control for Adaptive and Robust Robot Manipulation-Reference-Cited by-同舟云学术

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OSCAR: Data-Driven Operational Space Control for Adaptive and Robust Robot Manipulation

Published:2022-05-23 Issue: Volume: Page:
ISSN:
Container-title:2022 International Conference on Robotics and Automation (ICRA)
language:
Short-container-title:

Author:

Wong Josiah¹,Makoviychuk Viktor²,Anandkumar Anima²,Zhu Yuke²

Affiliation:

1. Stanford University

2. NVIDIA

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/9811522/9811357/09811967.pdf?arnumber=9811967

Reference53 articles.

1. Simplifying hamiltonian and lagrangian neural networks via explicit constraints;finzi;ArXiv eprint,2020

2. Reinforcement learning by reward-weighted regression for operational space control

3. Learning to Control in Operational Space

4. Robosuite: A modular simulation framework and benchmark for robot learning;zhu;ArXiv eprint,2020

Cited by 3 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. An event-driven Spike-DBN model for fault diagnosis using reward-STDP;ISA Transactions;2023-09

2. Decoupling Skill Learning from Robotic Control for Generalizable Object Manipulation;2023 IEEE International Conference on Robotics and Automation (ICRA);2023-05-29

3. Offline Reinforcement Learning of Robotic Control Using Deep Kinematics and Dynamics;IEEE/ASME Transactions on Mechatronics;2023

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