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A robotic learning and generalization framework for curved surface based on modified DMP

Xue, Xianfa; Dong, Jiale; Lu, Zhenyu; Wang, Ning

A robotic learning and generalization framework for curved surface based on modified DMP Thumbnail


Authors

Xianfa Xue

Jiale Dong

Zhenyu Lu



Abstract

How to reproduce and generalize the skills acquired by demonstrating is a hot topic for researchers. (1) A compliant continuous drag demonstration system based on discrete admittance model was designed to continuously and smoothly drag or demonstrate. (2) The modified DMP including the scaling factor and the force coupling term was used to improve the poor generalization ability of the classical DMP. (3) Curve drawing experiments were carried out to show the effectiveness of our proposed learning and generalization framework.

Citation

Xue, X., Dong, J., Lu, Z., & Wang, N. (2023). A robotic learning and generalization framework for curved surface based on modified DMP. Robotics and Autonomous Systems, 160, 104323. https://doi.org/10.1016/j.robot.2022.104323

Journal Article Type Article
Acceptance Date Nov 25, 2022
Online Publication Date Nov 29, 2022
Publication Date Feb 1, 2023
Deposit Date Dec 2, 2022
Publicly Available Date Dec 2, 2022
Journal Robotics and Autonomous Systems
Print ISSN 0921-8890
Publisher Elsevier
Peer Reviewed Peer Reviewed
Volume 160
Pages 104323
DOI https://doi.org/10.1016/j.robot.2022.104323
Keywords Computer Science Applications; General Mathematics; Software; Control and Systems Engineering; Continuous drag demonstration; Modified DMP; Curve drawing experiments; Learning and generalization framework
Public URL https://uwe-repository.worktribe.com/output/10198150
Publisher URL https://www.sciencedirect.com/science/article/pii/S0921889022002123?via%3Dihub

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