Robot learning system based on dynamic movement primitives and neural network

Zhang, Ying; Li, Miao; Yang, Chenguang

Abstract

In the process of Human-robot skill transfer, we require the robot to reproduce the trajectory of teacher and expect that the robot can generalize the learned trajectory. For the trajectory after generalization, we expect that the robot arm can accurately track. However, because the model of the robot can not be accurately obtained, some researchers have proposed using a neural network to approximate the unknown term. The parameters of the traditional RBF neural network are usually selected through the empirical and trial-and-error method, which maybe biased and inefficient. In addition, due to the end-effector of the mechanical arm trajectory will be constantly changing according to the needs of the task, when the neural network of compact set cannot contain the whole input vector, the neural network cannot achieve the ideal approximation effect. In this paper, the broad neural network is used to approximate the unknown terms of the robot. This method can reuse the motion controller that has been learned and complete other motions in the robot operating space without relearning its weight parameters. In this paper, the effectiveness of the proposed method is proved by the ultrasound scanning task.

Citation

Zhang, Y., Li, M., & Yang, C. (2021). Robot learning system based on dynamic movement primitives and neural network. Neurocomputing, 451, 205-214. https://doi.org/10.1016/j.neucom.2021.04.034

• Journal Article Type: Article
• Acceptance Date: Apr 10, 2021
• Online Publication Date: Apr 20, 2021
• Publication Date: Sep 3, 2021
• Deposit Date: Jun 22, 2021
• Publicly Available Date: Apr 21, 2022
• Journal: Neurocomputing
• Print ISSN: 0925-2312
• Electronic ISSN: 1872-8286
• Publisher: Elsevier
• Peer Reviewed: Peer Reviewed
• Volume: 451
• Pages: 205-214
• DOI: https://doi.org/10.1016/j.neucom.2021.04.034
• Keywords: Cognitive Neuroscience; Artificial Intelligence; Computer Science Applications
• Public URL: https://uwe-repository.worktribe.com/output/7485780
• Additional Information: This article is maintained by: Elsevier; Article Title: Robot learning system based on dynamic movement primitives and neural network; Journal Title: Neurocomputing; CrossRef DOI link to publisher maintained version: https://doi.org/10.1016/j.neucom.2021.04.034; Content Type: article; Copyright: © 2021 Elsevier B.V. All rights reserved.