Trajectory online adaption based on human motion prediction for teleoperation

Luo, Jing, Huang, Darong, Li, Yanan and Yang, Chenguang (2021) Trajectory online adaption based on human motion prediction for teleoperation. IEEE Transactions on Automation Science and Engineering. pp. 1-8. ISSN 1545-5955

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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.

Item Type: Article
Additional Information: © 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.
Schools and Departments: School of Engineering and Informatics > Engineering and Design
SWORD Depositor: Mx Elements Account
Depositing User: Mx Elements Account
Date Deposited: 09 Sep 2021 07:44
Last Modified: 11 Jan 2022 09:15
URI: http://sro.sussex.ac.uk/id/eprint/101576

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