Weiyong Si
A framework for composite layup skill learning and generalizing through teleoperation
Si, Weiyong; Wang, Ning; Li, Qinchuan; Yang, Chenguang
Authors
Dr. Ning Wang Ning2.Wang@uwe.ac.uk
Senior Lecturer in Robotics
Qinchuan Li
Charlie Yang Charlie.Yang@uwe.ac.uk
Professor in Robotics
Abstract
In this article, an impedance control-based framework for human-robot composite layup skill transfer was developed, and the human-in-the-loop mechanism was investigated to achieve human-robot skill transfer. Although there are some works on human-robot skill transfer, it is still difficult to transfer the manipulation skill to robots through teleoperation efficiently and intuitively. In this article, we developed an impedance-based control architecture of telemanipulation in task space for the human-robot skill transfer through teleoperation. This framework not only achieves human-robot skill transfer but also provides a solution to human-robot collaboration through teleoperation. The variable impedance control system enables the compliant interaction between the robot and the environment, smooth transition between different stages. Dynamic movement primitives based learning from demonstration (LfD) is employed to model the human manipulation skills, and the learned skill can be generalized to different tasks and environments, such as the different shapes of components and different orientations of components. The performance of the proposed approach is evaluated on a 7 DoF Franka Panda through the robot-assisted composite layup on different shapes and orientations of the components.
Citation
Si, W., Wang, N., Li, Q., & Yang, C. (2022). A framework for composite layup skill learning and generalizing through teleoperation. Frontiers in Neurorobotics, 16, Article 840240. https://doi.org/10.3389/fnbot.2022.840240
Journal Article Type | Article |
---|---|
Acceptance Date | Jan 6, 2022 |
Online Publication Date | Feb 11, 2022 |
Publication Date | Feb 11, 2022 |
Deposit Date | Jul 22, 2022 |
Publicly Available Date | Jul 26, 2022 |
Journal | Frontiers in Neurorobotics |
Electronic ISSN | 1662-5218 |
Publisher | Frontiers Media |
Peer Reviewed | Peer Reviewed |
Volume | 16 |
Article Number | 840240 |
DOI | https://doi.org/10.3389/fnbot.2022.840240 |
Keywords | Artificial Intelligence; Biomedical Engineering; semi-autonomous composite layup, human-in-the-loo p, dynamic movement primitives, learning from demonstration, teleoperation |
Public URL | https://uwe-repository.worktribe.com/output/9720116 |
Publisher URL | https://www.frontiersin.org/articles/10.3389/fnbot.2022.840240/full |
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A framework for composite layup skill learning and generalizing through teleoperation
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Licence
http://creativecommons.org/licenses/by/4.0/
Publisher Licence URL
http://creativecommons.org/licenses/by/4.0/
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