Residual Learning From Demonstration: Adapting DMPs for Contact-Rich Manipulation-Reference-Cited by-同舟云学术

Residual Learning From Demonstration: Adapting DMPs for Contact-Rich Manipulation

Published:2022-04 Issue:2 Volume:7 Page:4488-4495
ISSN:2377-3766
Container-title:IEEE Robotics and Automation Letters
language:
Short-container-title:IEEE Robot. Autom. Lett.

Author:

Davchev Todor¹^ORCID,Luck Kevin Sebastian²,Burke Michael³^ORCID,Meier Franziska⁴^ORCID,Schaal Stefan⁵,Ramamoorthy Subramanian¹^ORCID

Affiliation:

1. School of Informatics, University of Edinburgh, Edinburgh, U.K.

2. Department of Electrical Engineering and Automation, Intelligent Robotics, Aalto University, Espoo, Finland

3. ECSE, Monash University, Melbourne, Australia

4. Facebook AI Research, Menlo Park, CA, USA

5. [Google X] Intrinsic, Mountain View, CA, USA

Funder

EPSRC iCASE Award with Thales Maritime Systems

EPSRC U.K. RAI Hub NCNR

Academy of Finland

Alan Turing Institute

University of Edinburgh

Google X AI Residency

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Artificial Intelligence,Control and Optimization,Computer Science Applications,Computer Vision and Pattern Recognition,Mechanical Engineering,Human-Computer Interaction,Biomedical Engineering,Control and Systems Engineering

Link

http://xplorestaging.ieee.org/ielx7/7083369/9647862/09709544.pdf?arnumber=9709544

Reference36 articles.

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