Jing Luo
Trajectory online adaption based on human motion prediction for teleoperation
Luo, Jing; Huang, Darong; Li, Yanan; Yang, Chenguang
Abstract
In this work, a human motion intention prediction method based on an autoregressive (AR) model for teleoperation is developed. Based on this method, the robot's motion trajectory can be updated in real time through updating the parameters of the AR model. In the teleoperated robot's control loop, a virtual force model is defined to describe the interaction profile and to correct the robot's motion trajectory in real time. The proposed human motion prediction algorithm acts as a feedforward model to update the robot's motion and to revise this motion in the process of human-robot interaction (HRI). The convergence of this method is analyzed theoretically. Comparative studies demonstrate the enhanced performance of the proposed approach.
Citation
Luo, J., Huang, D., Li, Y., & Yang, C. (2022). Trajectory online adaption based on human motion prediction for teleoperation. IEEE Transactions on Automation Science and Engineering, 19(4), 3184-3191. https://doi.org/10.1109/tase.2021.3111678
Journal Article Type | Article |
---|---|
Acceptance Date | Sep 5, 2021 |
Online Publication Date | Sep 20, 2021 |
Publication Date | Oct 1, 2022 |
Deposit Date | Sep 22, 2021 |
Publicly Available Date | Sep 23, 2021 |
Journal | IEEE Transactions on Automation Science and Engineering |
Print ISSN | 1545-5955 |
Electronic ISSN | 1558-3783 |
Publisher | Institute of Electrical and Electronics Engineers |
Peer Reviewed | Peer Reviewed |
Volume | 19 |
Issue | 4 |
Pages | 3184-3191 |
DOI | https://doi.org/10.1109/tase.2021.3111678 |
Keywords | Electrical and Electronic Engineering; Control and Systems Engineering |
Public URL | https://uwe-repository.worktribe.com/output/7830885 |
Publisher URL | https://ieeexplore.ieee.org/document/9541105 |
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Copyright Statement
This is the author’s accepted manuscript. The final published version is available here: https://ieeexplore.ieee.org/document/9541105
10.1109/TASE.2021.3111678
© 2021 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
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