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Neural Control of Bimanual Robots With Guaranteed Global Stability and Motion Precision

Chenguang Yang, Yiming Jiang, Zhijun Li, Wei He, Chun-Yi Su

IEEE Transactions on Industrial Informatics, Volume: 13, Issue: 3, Pages: 1162 - 1171

Swansea University Author: Chenguang Yang

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DOI (Published version): 10.1109/TII.2016.2612646

Abstract

Robots with coordinated dual arms are able to perform more complicated tasks that a single manipulator could hardly achieve. However, more rigorous motion precision is required to guarantee effective cooperation between the dual arms, especially when they grasp a common object. In this case, the int...

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Published in: IEEE Transactions on Industrial Informatics
ISSN: 1551-3203 1941-0050
Published: 2017
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URI: https://cronfa.swan.ac.uk/Record/cronfa39396
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first_indexed 2018-04-13T19:29:16Z
last_indexed 2018-05-22T19:00:53Z
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spelling 2018-05-22T15:04:55.9245859 v2 39396 2018-04-13 Neural Control of Bimanual Robots With Guaranteed Global Stability and Motion Precision d2a5024448bfac00a9b3890a8404380b Chenguang Yang Chenguang Yang true false 2018-04-13 EEN Robots with coordinated dual arms are able to perform more complicated tasks that a single manipulator could hardly achieve. However, more rigorous motion precision is required to guarantee effective cooperation between the dual arms, especially when they grasp a common object. In this case, the internal forces applied on the object must also be considered in addition to the external forces. Therefore, a prescribed tracking performance at both transient and steady states is first specified, and then, a controller is synthesized to rigorously guarantee the specified motion performance. In the presence of unknown dynamics of both the robot arms and the manipulated object, the neural network approximation technique is employed to compensate for uncertainties. In order to extend the semiglobal stability achieved by conventional neural control to global stability, a switching mechanism is integrated into the control design. Effectiveness of the proposed control design has been shown through experiments carried out on the Baxter Robot. Journal Article IEEE Transactions on Industrial Informatics 13 3 1162 1171 1551-3203 1941-0050 31 12 2017 2017-12-31 10.1109/TII.2016.2612646 COLLEGE NANME Engineering COLLEGE CODE EEN Swansea University 2018-05-22T15:04:55.9245859 2018-04-13T15:07:15.3504575 Faculty of Science and Engineering School of Engineering and Applied Sciences - Uncategorised Chenguang Yang 1 Yiming Jiang 2 Zhijun Li 3 Wei He 4 Chun-Yi Su 5 0039396-13042018151103.pdf ALL_TII-16-0565.pdf 2018-04-13T15:11:03.3330000 Output 3093387 application/pdf Accepted Manuscript true 2018-04-13T00:00:00.0000000 true eng
title Neural Control of Bimanual Robots With Guaranteed Global Stability and Motion Precision
spellingShingle Neural Control of Bimanual Robots With Guaranteed Global Stability and Motion Precision
Chenguang Yang
title_short Neural Control of Bimanual Robots With Guaranteed Global Stability and Motion Precision
title_full Neural Control of Bimanual Robots With Guaranteed Global Stability and Motion Precision
title_fullStr Neural Control of Bimanual Robots With Guaranteed Global Stability and Motion Precision
title_full_unstemmed Neural Control of Bimanual Robots With Guaranteed Global Stability and Motion Precision
title_sort Neural Control of Bimanual Robots With Guaranteed Global Stability and Motion Precision
author_id_str_mv d2a5024448bfac00a9b3890a8404380b
author_id_fullname_str_mv d2a5024448bfac00a9b3890a8404380b_***_Chenguang Yang
author Chenguang Yang
author2 Chenguang Yang
Yiming Jiang
Zhijun Li
Wei He
Chun-Yi Su
format Journal article
container_title IEEE Transactions on Industrial Informatics
container_volume 13
container_issue 3
container_start_page 1162
publishDate 2017
institution Swansea University
issn 1551-3203
1941-0050
doi_str_mv 10.1109/TII.2016.2612646
college_str Faculty of Science and Engineering
hierarchytype
hierarchy_top_id facultyofscienceandengineering
hierarchy_top_title Faculty of Science and Engineering
hierarchy_parent_id facultyofscienceandengineering
hierarchy_parent_title Faculty of Science and Engineering
department_str School of Engineering and Applied Sciences - Uncategorised{{{_:::_}}}Faculty of Science and Engineering{{{_:::_}}}School of Engineering and Applied Sciences - Uncategorised
document_store_str 1
active_str 0
description Robots with coordinated dual arms are able to perform more complicated tasks that a single manipulator could hardly achieve. However, more rigorous motion precision is required to guarantee effective cooperation between the dual arms, especially when they grasp a common object. In this case, the internal forces applied on the object must also be considered in addition to the external forces. Therefore, a prescribed tracking performance at both transient and steady states is first specified, and then, a controller is synthesized to rigorously guarantee the specified motion performance. In the presence of unknown dynamics of both the robot arms and the manipulated object, the neural network approximation technique is employed to compensate for uncertainties. In order to extend the semiglobal stability achieved by conventional neural control to global stability, a switching mechanism is integrated into the control design. Effectiveness of the proposed control design has been shown through experiments carried out on the Baxter Robot.
published_date 2017-12-31T03:50:01Z
_version_ 1763752439415046144
score 11.036706

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