Robotic Impedance Learning for Robot-Assisted Physical Training
Impedance control has been widely used in robotic applications where a robot has physical interaction with its environment. However, how the impedance parameters are adapted according to the context of a task is still an open problem. In this paper, we focus on a physical training scenario, where th...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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Frontiers Media S.A.
2019-08-01
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| Series: | Frontiers in Robotics and AI |
| Subjects: | |
| Online Access: | https://www.frontiersin.org/article/10.3389/frobt.2019.00078/full |
| _version_ | 1819237421835878400 |
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| author | Yanan Li Xiaodong Zhou Junpei Zhong Xuefang Li |
| author_facet | Yanan Li Xiaodong Zhou Junpei Zhong Xuefang Li |
| author_sort | Yanan Li |
| collection | DOAJ |
| description | Impedance control has been widely used in robotic applications where a robot has physical interaction with its environment. However, how the impedance parameters are adapted according to the context of a task is still an open problem. In this paper, we focus on a physical training scenario, where the robot needs to adjust its impedance parameters according to the human user's performance so as to promote their learning. This is a challenging problem as humans' dynamic behaviors are difficult to model and subject to uncertainties. Considering that physical training usually involves a repetitive process, we develop impedance learning in physical training by using iterative learning control (ILC). Since the condition of the same iteration length in traditional ILC cannot be met due to human variance, we adopt a novel ILC to deal with varying iteration lengthes. By theoretical analysis and simulations, we show that the proposed method can effectively learn the robot's impedance in the application of robot-assisted physical training. |
| first_indexed | 2024-12-23T13:20:04Z |
| format | Article |
| id | doaj.art-80a106fc0e67409bb57b29f0735e64bb |
| institution | Directory Open Access Journal |
| issn | 2296-9144 |
| language | English |
| last_indexed | 2024-12-23T13:20:04Z |
| publishDate | 2019-08-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Robotics and AI |
| spelling | doaj.art-80a106fc0e67409bb57b29f0735e64bb2022-12-21T17:45:30ZengFrontiers Media S.A.Frontiers in Robotics and AI2296-91442019-08-01610.3389/frobt.2019.00078470691Robotic Impedance Learning for Robot-Assisted Physical TrainingYanan Li0Xiaodong Zhou1Junpei Zhong2Xuefang Li3Department of Engineering and Design, University of Sussex, Brighton, United KingdomBeijing Institute of Control Engineering, Beijing, ChinaSchool of Science and Technology, Nottingham Trent University, Nottingham, United KingdomDepartment of Electrical Engineering, Imperial College of Science, Technology and Medicine, London, United KingdomImpedance control has been widely used in robotic applications where a robot has physical interaction with its environment. However, how the impedance parameters are adapted according to the context of a task is still an open problem. In this paper, we focus on a physical training scenario, where the robot needs to adjust its impedance parameters according to the human user's performance so as to promote their learning. This is a challenging problem as humans' dynamic behaviors are difficult to model and subject to uncertainties. Considering that physical training usually involves a repetitive process, we develop impedance learning in physical training by using iterative learning control (ILC). Since the condition of the same iteration length in traditional ILC cannot be met due to human variance, we adopt a novel ILC to deal with varying iteration lengthes. By theoretical analysis and simulations, we show that the proposed method can effectively learn the robot's impedance in the application of robot-assisted physical training.https://www.frontiersin.org/article/10.3389/frobt.2019.00078/fullimpedance learningimpedance controliterative learning controlphysical human-robot interactionrobotic control |
| spellingShingle | Yanan Li Xiaodong Zhou Junpei Zhong Xuefang Li Robotic Impedance Learning for Robot-Assisted Physical Training Frontiers in Robotics and AI impedance learning impedance control iterative learning control physical human-robot interaction robotic control |
| title | Robotic Impedance Learning for Robot-Assisted Physical Training |
| title_full | Robotic Impedance Learning for Robot-Assisted Physical Training |
| title_fullStr | Robotic Impedance Learning for Robot-Assisted Physical Training |
| title_full_unstemmed | Robotic Impedance Learning for Robot-Assisted Physical Training |
| title_short | Robotic Impedance Learning for Robot-Assisted Physical Training |
| title_sort | robotic impedance learning for robot assisted physical training |
| topic | impedance learning impedance control iterative learning control physical human-robot interaction robotic control |
| url | https://www.frontiersin.org/article/10.3389/frobt.2019.00078/full |
| work_keys_str_mv | AT yananli roboticimpedancelearningforrobotassistedphysicaltraining AT xiaodongzhou roboticimpedancelearningforrobotassistedphysicaltraining AT junpeizhong roboticimpedancelearningforrobotassistedphysicaltraining AT xuefangli roboticimpedancelearningforrobotassistedphysicaltraining |