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A Novel Algorithm for Robust Calibration of Kinematic Manipulators and its Experimental Validation

Chentao Mao, Shuai Li Orcid Logo, Zhangwei Chen, Hongfei Zu, Zhirong Wang, Yuxiang Wang

IEEE Access, Volume: 7, Pages: 90487 - 90496

Swansea University Author: Shuai Li Orcid Logo

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DOI (Published version): 10.1109/access.2019.2926801

Abstract

Kinematic calibration of manipulators is an efficient and fundamental way to ensure reliability and high performance of robots. Research on kinematic calibration has a long tradition, and a common strategy used for calibration is to guarantee the least errors in the sense of root-mean-square deviati...

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Published in: IEEE Access
ISSN: 2169-3536 2169-3536
Published: 2019
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spelling 2021-01-15T10:24:06.6040523 v2 52004 2019-09-23 A Novel Algorithm for Robust Calibration of Kinematic Manipulators and its Experimental Validation 42ff9eed09bcd109fbbe484a0f99a8a8 0000-0001-8316-5289 Shuai Li Shuai Li true false 2019-09-23 MECH Kinematic calibration of manipulators is an efficient and fundamental way to ensure reliability and high performance of robots. Research on kinematic calibration has a long tradition, and a common strategy used for calibration is to guarantee the least errors in the sense of root-mean-square deviation. However, the absolute positioning accuracy is determined by the maximum error of manipulators, and it is a key indicator for evaluating performance. For example, using manipulators to print machine elements, obviously where the error is the most, may likely cause inaccurate fit. Hence, it is crucial to study a robust calibration strategy. Considering the calibration problem, both positioning and orientation accuracy are ensured by minimizing the maximum positioning errors of three spherical mounted retro-reflectors (SMRs) on the end effector of manipulators. Unfortunately, traditional optimization methods based on gradient cannot be directly employed to solve the minimax problem. Due to the recent progress on optimization, researchers found that the minimax can be transformed into sequence quadratic programming problems under inequality conditions, thus providing solutions for solving the robust calibration. This paper applied this method to convert the calibration problem into constrained quadratic subproblems, and the subproblems can be solved through the primal-dual subgradient method. Then, convexity and robustness analysis is given to prove that these subproblems can quickly converge to a local minimum. Finally, to verify the validity of the proposed algorithm, the experiments are conducted on an IRB 2600 manipulator, and the results show that, with the minimax search algorithm, both the positioning and orientation accuracy is enhanced by 67.34% and 73.14%, respectively, which is significantly higher than the performance of the single-SMR calibration algorithm widely used in the field of industry. Journal Article IEEE Access 7 90487 90496 2169-3536 2169-3536 24 7 2019 2019-07-24 10.1109/access.2019.2926801 COLLEGE NANME Mechanical Engineering COLLEGE CODE MECH Swansea University 2021-01-15T10:24:06.6040523 2019-09-23T11:49:08.9092901 Faculty of Science and Engineering School of Aerospace, Civil, Electrical, General and Mechanical Engineering - Mechanical Engineering Chentao Mao 1 Shuai Li 0000-0001-8316-5289 2 Zhangwei Chen 3 Hongfei Zu 4 Zhirong Wang 5 Yuxiang Wang 6 0052004-10102019114833.pdf mao2019.pdf 2019-10-10T11:48:33.8370000 Output 1640711 application/pdf Version of Record true This work is licensed under a Creative Commons Attribution 4.0 License. true eng http://creativecommons.org/licenses/by/4.0/
title A Novel Algorithm for Robust Calibration of Kinematic Manipulators and its Experimental Validation
spellingShingle A Novel Algorithm for Robust Calibration of Kinematic Manipulators and its Experimental Validation
Shuai Li
title_short A Novel Algorithm for Robust Calibration of Kinematic Manipulators and its Experimental Validation
title_full A Novel Algorithm for Robust Calibration of Kinematic Manipulators and its Experimental Validation
title_fullStr A Novel Algorithm for Robust Calibration of Kinematic Manipulators and its Experimental Validation
title_full_unstemmed A Novel Algorithm for Robust Calibration of Kinematic Manipulators and its Experimental Validation
title_sort A Novel Algorithm for Robust Calibration of Kinematic Manipulators and its Experimental Validation
author_id_str_mv 42ff9eed09bcd109fbbe484a0f99a8a8
author_id_fullname_str_mv 42ff9eed09bcd109fbbe484a0f99a8a8_***_Shuai Li
author Shuai Li
author2 Chentao Mao
Shuai Li
Zhangwei Chen
Hongfei Zu
Zhirong Wang
Yuxiang Wang
format Journal article
container_title IEEE Access
container_volume 7
container_start_page 90487
publishDate 2019
institution Swansea University
issn 2169-3536
2169-3536
doi_str_mv 10.1109/access.2019.2926801
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 Aerospace, Civil, Electrical, General and Mechanical Engineering - Mechanical Engineering{{{_:::_}}}Faculty of Science and Engineering{{{_:::_}}}School of Aerospace, Civil, Electrical, General and Mechanical Engineering - Mechanical Engineering
document_store_str 1
active_str 0
description Kinematic calibration of manipulators is an efficient and fundamental way to ensure reliability and high performance of robots. Research on kinematic calibration has a long tradition, and a common strategy used for calibration is to guarantee the least errors in the sense of root-mean-square deviation. However, the absolute positioning accuracy is determined by the maximum error of manipulators, and it is a key indicator for evaluating performance. For example, using manipulators to print machine elements, obviously where the error is the most, may likely cause inaccurate fit. Hence, it is crucial to study a robust calibration strategy. Considering the calibration problem, both positioning and orientation accuracy are ensured by minimizing the maximum positioning errors of three spherical mounted retro-reflectors (SMRs) on the end effector of manipulators. Unfortunately, traditional optimization methods based on gradient cannot be directly employed to solve the minimax problem. Due to the recent progress on optimization, researchers found that the minimax can be transformed into sequence quadratic programming problems under inequality conditions, thus providing solutions for solving the robust calibration. This paper applied this method to convert the calibration problem into constrained quadratic subproblems, and the subproblems can be solved through the primal-dual subgradient method. Then, convexity and robustness analysis is given to prove that these subproblems can quickly converge to a local minimum. Finally, to verify the validity of the proposed algorithm, the experiments are conducted on an IRB 2600 manipulator, and the results show that, with the minimax search algorithm, both the positioning and orientation accuracy is enhanced by 67.34% and 73.14%, respectively, which is significantly higher than the performance of the single-SMR calibration algorithm widely used in the field of industry.
published_date 2019-07-24T04:04:07Z
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score 11.037603

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