Dexterous robotic manipulation using deep reinforcement learning and knowledge transfer for complex sparse reward‐based tasks-Reference-Cited by-同舟云学术

Dexterous robotic manipulation using deep reinforcement learning and knowledge transfer for complex sparse reward‐based tasks

Published:2022-11-30 Issue: Volume: Page:
ISSN:0266-4720
Container-title:Expert Systems
language:en
Short-container-title:Expert Systems

Author:

Wang Qiang¹^ORCID,Sanchez Francisco Roldan²³,McCarthy Robert¹^ORCID,Bulens David Cordova¹^ORCID,McGuinness Kevin²³^ORCID,O'Connor Noel²³^ORCID,Wüthrich Manuel⁴,Widmaier Felix⁵^ORCID,Bauer Stefan⁶^ORCID,Redmond Stephen J.¹³^ORCID

Affiliation:

1. University College Dublin Dublin Ireland

2. Dublin City University Dublin Ireland

3. Insight SFI Research Centre for Data Analytics Dublin Ireland

4. Harvard University Cambridge Massachusetts USA

5. MPI for Intelligent Systems Tübingen Germany

6. KTH Stockholm Stockholm Sweden

Funder

China Scholarship Council

Science Foundation Ireland

Publisher

Wiley

Subject

Artificial Intelligence,Computational Theory and Mathematics,Theoretical Computer Science,Control and Systems Engineering

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1111/exsy.13205

Reference42 articles.

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2. Allshire A. Mittal M. Lodaya V. Makoviychuk V. Makoviichuk D. Widmaier F. Wüthrich M. Bauer S. Handa A. &Garg A.(2021).Transferring dexterous manipulation from GPU simulation to a remote real‐world TriFinger.arXiv preprint arXiv:2108.09779.

3. Hindsight experience replay;Andrychowicz M.;Advances in Neural Information Processing Systems,2017

4. Learning dexterous in-hand manipulation

5. Meta Reinforcement Learning for Sim-to-real Domain Adaptation

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