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An efficient self-motion scheme for redundant robot manipulators: a varying-gain neural self-motion approach

Content Provider	Scilit
Author	Zhang, Pengchao Ren, Xiaohui Zhang, Zhijun
Copyright Year	2021
Description	In order to achieve high efficient self-motion for a redundant robot manipulator, a novel quadratic programming and varying-gain recurrent neural network based varying-gain neural self-motion (VGN-SM) approach is proposed and developed. With VGN-SM, the convergence errors can be adaptively and efficiently converged to zero. For comparisons, a traditional fixed-parameter neural self-motion (FPN-SM) approach is also presented. Theoretical analysis shows that the proposed VGN-SM has higher accuracy than the traditional FPN-SM. Finally, comparative experiments between VGN-SM and FPN-SM are performed on a six degrees-of-freedom robot manipulator to verify the advantages of the novel VGN-SM.
Related Links	https://www.cambridge.org/core/services/aop-cambridge-core/content/view/7A9C47FD73A839360848AD356DB87175/S0263574721000047a.pdf/div-class-title-an-efficient-self-motion-scheme-for-redundant-robot-manipulators-a-varying-gain-neural-self-motion-approach-div.pdf
Ending Page	1908
Page Count	12
Starting Page	1897
ISSN	02635747
e-ISSN	14698668
DOI	10.1017/s0263574721000047
Journal	Robotica
Issue Number	10
Volume Number	39
Language	English
Publisher	Cambridge University Press (CUP)
Publisher Date	2021-10-01
Access Restriction	Open
Subject Keyword	Robotica gain Recurrent Neural Network Zeroing Neural Network
Content Type	Text
Resource Type	Article
Subject	Control and Optimization Artificial Intelligence Rehabilitation Control and Systems Engineering Mechanical Engineering Computational Mechanics Modeling and Simulation Computer Science Applications Computer Vision and Pattern Recognition Software

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1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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9	IDR Setup or Support	Queries related to establishment and support of Institutional Digital Repository (IDR) and IDR workshops	idr@ndl.gov.in

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