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A novel human-robot skill transfer method for contact-rich manipulation task

Dong, Jiale; Si, Weiyong; Yang, Chenguang

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Authors

Jiale Dong

Weiyong Si



Abstract

Purpose: The purpose of this paper is to enhance the robot’s ability to complete multi-step contact tasks in unknown or dynamic environments, as well as the generalization ability of the same task in different environments. Design/methodology/approach: This paper proposes a framework that combines learning from demonstration (LfD), behavior tree (BT) and broad learning system (BLS). First, the original dynamic motion primitive is modified to have a better generalization ability for representing motion primitives. Then, a BT based on tasks is constructed, which will select appropriate motion primitives according to the environment state and robot ontology state, and then the BLS will generate specific parameters of the motion primitives based on the state. The weights of the BLS can also be optimized after each successful execution. Findings: The authors carried out the tasks of cleaning the desktop and assembling the shaft hole on Baxter and Elite robots, respectively, and both tasks were successfully completed, which proved the effectiveness of the framework. Originality/value: This paper proposes a framework that combines LfD, BT and BLS. To the best of the authors’ knowledge, no similar methods were found in other people’s work. Therefore, the authors believe that this work is original.

Citation

Dong, J., Si, W., & Yang, C. (2023). A novel human-robot skill transfer method for contact-rich manipulation task. Robotic Intelligence and Automation, 43(3), https://doi.org/10.1108/RIA-01-2023-0002

Journal Article Type Article
Acceptance Date May 15, 2023
Online Publication Date Jun 7, 2023
Publication Date Jun 23, 2023
Deposit Date Jun 27, 2023
Publicly Available Date Jun 8, 2024
Journal Robotic Intelligence and Automation
Print ISSN 2754-6969
Electronic ISSN 2754-6977
Publisher Emerald
Peer Reviewed Peer Reviewed
Volume 43
Issue 3
DOI https://doi.org/10.1108/RIA-01-2023-0002
Keywords Skill learning, Broad learning system, Behavior tree, Assembling, Dynamic motion primitives
Public URL https://uwe-repository.worktribe.com/output/10890457
Publisher URL https://www.emerald.com/insight/content/doi/10.1108/RIA-01-2023-0002/full/html

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Licence
http://creativecommons.org/licenses/by-nc/4.0/

Publisher Licence URL
http://creativecommons.org/licenses/by-nc/4.0/

Copyright Statement
This is the authors accepted version of the article ‘Dong, J., Si, W., & Yang, C. (2023). A novel human-robot skill transfer method for contact-rich manipulation task. Robotic Intelligence and Automation, 43(3)’.

DOI: https://doi.org/10.1108/RIA-01-2023-0002

The final published version is available here: https://www.emerald.com/insight/content/doi/10.1108/RIA-01-2023-0002/full/html

Publisher: Emerald Publishing Limited
Copyright © 2023, Emerald Publishing Limited





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