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Kinematic calibration of a 6-DOF hybrid robot by considering multicollinearity in the identification Jacobian
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Huang, Tian, Zhao, Dong, Yin, Fuwen, Tian, Wenjie and Chetwynd, D. G. (2019) Kinematic calibration of a 6-DOF hybrid robot by considering multicollinearity in the identification Jacobian. Mechanism and Machine Theory, 131 . pp. 371-384. doi:10.1016/j.mechmachtheory.2018.10.008 ISSN 0094-114X.
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WRAP-kinematic-calibration-hybrid-multicollinearity-Jacobian-Chetwynd-2018.pdf - Accepted Version - Requires a PDF viewer. Available under License Creative Commons Attribution Non-commercial No Derivatives 4.0. Download (1388Kb) | Preview |
Official URL: http://dx.doi.org/10.1016/j.mechmachtheory.2018.10...
Abstract
This paper presents a systematic approach for the kinematic calibration of a 6-DOF hybrid polishing robot. It concentrates particularly on dealing with ill-conditioning that arises from multicollinearity in the identification Jacobian as a consequence of limited pose measurements. A linearized error model is formulated, using screw theory, by considering all possible source errors at the joint/link level. Calibration is based upon pose error measurements captured using a laser tracker when the polishing head undergoes pure translation within the task workspace. A two-step procedure for error parameter estimation and pose error compensation is then proposed: (1) coarse estimation and compensation of the encoder offsets using linear least squares; and (2) fine estimation of the whole set of identifiable error parameters using a Liu estimation and subsequent modification of the NC trajectory dataset of the polishing head. Both simulations and experiments on a prototype machine show that the overall standard deviation of the error parameters identified by Liu estimator is much less than that estimated by linear least squares, confirming its greater robustness in the presence of measurement uncertainty. The proposed approach results in satisfactory pose accuracy of the polishing head throughout the entire task workspace.
Item Type: | Journal Article | |||||||||||||||
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Subjects: | Q Science > QA Mathematics T Technology > TJ Mechanical engineering and machinery |
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Divisions: | Faculty of Science, Engineering and Medicine > Engineering > Engineering | |||||||||||||||
Library of Congress Subject Headings (LCSH): | Robots -- Calibration, Jacobians -- Industrial applications, Robotics | |||||||||||||||
Journal or Publication Title: | Mechanism and Machine Theory | |||||||||||||||
Publisher: | Pergamon-Elsevier Science Ltd. | |||||||||||||||
ISSN: | 0094-114X | |||||||||||||||
Official Date: | January 2019 | |||||||||||||||
Dates: |
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Volume: | 131 | |||||||||||||||
Page Range: | pp. 371-384 | |||||||||||||||
DOI: | 10.1016/j.mechmachtheory.2018.10.008 | |||||||||||||||
Status: | Peer Reviewed | |||||||||||||||
Publication Status: | Published | |||||||||||||||
Access rights to Published version: | Restricted or Subscription Access | |||||||||||||||
Date of first compliant deposit: | 13 December 2018 | |||||||||||||||
Date of first compliant Open Access: | 16 October 2019 | |||||||||||||||
RIOXX Funder/Project Grant: |
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