Learning a Flexible Neural Energy Function With a Unique Minimum for Globally Stable and Accurate Demonstration Learning-Reference-Cited by-同舟云学术

Learning a Flexible Neural Energy Function With a Unique Minimum for Globally Stable and Accurate Demonstration Learning

Published:2023-12 Issue:6 Volume:39 Page:4520-4538
ISSN:1552-3098
Container-title:IEEE Transactions on Robotics
language:
Short-container-title:IEEE Trans. Robot.

Author:

Jin Zhehao¹^ORCID,Si Weiyong²^ORCID,Liu Andong¹^ORCID,Zhang Wen-An¹^ORCID,Yu Li¹^ORCID,Yang Chenguang²^ORCID

Affiliation:

1. Zhejiang Provincial United Key Laboratory of Embedded Systems, Department of Information Engineering, Zhejiang University of Technology, Hangzhou, China

2. Bristol Robotics Laboratory, University of the West of England, Bristol, U.K.

Funder

Zhejiang Provincial Natural Science Foundation of China

National Natural Science Foundation of China

China Scholarship Council

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Electrical and Electronic Engineering,Computer Science Applications,Control and Systems Engineering

Link

http://xplorestaging.ieee.org/ielx7/8860/10352149/10226460.pdf?arnumber=10226460

Reference50 articles.

1. Impedance Control Architecture for Robotic-Assisted Mold Polishing Based on Human Demonstration

2. Efficient Insertion Control for Precision Assembly Based on Demonstration Learning and Reinforcement Learning

3. A Human-Like Dual-Forklift Collaborative Mechanism for Container Handling

4. Decomposition of human motion into dynamics-based primitives with application to drawing tasks

5. Human-Like Adaptation of Force and Impedance in Stable and Unstable Interactions

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