Kinematic self-calibration of a 3-DOF parallel mechanism with ill-conditioned identification matrix

Xingguang Duan; Lixing Jin; Changsheng Li; Rui He; Quanbin Lai; Rui Ma

doi:10.1109/RCAR52367.2021.9517431

Kinematic self-calibration of a 3-DOF parallel mechanism with ill-conditioned identification matrix

Xingguang Duan, Lixing Jin^*, Changsheng Li, Rui He, Quanbin Lai, Rui Ma

^*此作品的通讯作者

机电学院

Beijing Institute of Technology

科研成果: 书/报告/会议事项章节 › 会议稿件 › 同行评审

摘要

Kinematics calibration is an effective means to improve the accuracy of the mechanism. Parallel mechanisms with redundant actuation have potential for kinematic self-calibration. In this paper, the self-calibration algorithms of a parallel mechanism with 3-DOF are studied. The Jacobian matrix for self-calibration is ill-posed/ill-condition caused by multicollinearity between kinematics parameter, and the calculation with least square method diverges. Truncated singular value decomposition (TSVD), ridge regression (RR) and Liu estimation algorithm are utilized to address this problem, and the identification performances under different error parameters are compared.

源语言	英语
主期刊名	2021 IEEE International Conference on Real-Time Computing and Robotics, RCAR 2021
出版商	Institute of Electrical and Electronics Engineers Inc.
页	314-318
页数	5
ISBN（电子版）	9781665436786
DOI	https://doi.org/10.1109/RCAR52367.2021.9517431
出版状态	已出版 - 15 7月 2021
活动	2021 IEEE International Conference on Real-Time Computing and Robotics, RCAR 2021 - Xining, 中国期限: 15 7月 2021 → 19 7月 2021

出版系列

姓名	2021 IEEE International Conference on Real-Time Computing and Robotics, RCAR 2021

会议

会议	2021 IEEE International Conference on Real-Time Computing and Robotics, RCAR 2021
国家/地区	中国
市	Xining
时期	15/07/21 → 19/07/21

访问文件

10.1109/RCAR52367.2021.9517431

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链接到 Scopus 的出版物

引用此

Duan, X., Jin, L., Li, C., He, R., Lai, Q., & Ma, R. (2021). Kinematic self-calibration of a 3-DOF parallel mechanism with ill-conditioned identification matrix. 在 2021 IEEE International Conference on Real-Time Computing and Robotics, RCAR 2021 (页码 314-318). (2021 IEEE International Conference on Real-Time Computing and Robotics, RCAR 2021). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/RCAR52367.2021.9517431

Duan, Xingguang ; Jin, Lixing ; Li, Changsheng 等. / Kinematic self-calibration of a 3-DOF parallel mechanism with ill-conditioned identification matrix. 2021 IEEE International Conference on Real-Time Computing and Robotics, RCAR 2021. Institute of Electrical and Electronics Engineers Inc., 2021. 页码 314-318 (2021 IEEE International Conference on Real-Time Computing and Robotics, RCAR 2021).

@inproceedings{cba5f6a243c44e219ee72c5e1377f2d2,

title = "Kinematic self-calibration of a 3-DOF parallel mechanism with ill-conditioned identification matrix",

abstract = "Kinematics calibration is an effective means to improve the accuracy of the mechanism. Parallel mechanisms with redundant actuation have potential for kinematic self-calibration. In this paper, the self-calibration algorithms of a parallel mechanism with 3-DOF are studied. The Jacobian matrix for self-calibration is ill-posed/ill-condition caused by multicollinearity between kinematics parameter, and the calculation with least square method diverges. Truncated singular value decomposition (TSVD), ridge regression (RR) and Liu estimation algorithm are utilized to address this problem, and the identification performances under different error parameters are compared.",

author = "Xingguang Duan and Lixing Jin and Changsheng Li and Rui He and Quanbin Lai and Rui Ma",

note = "Publisher Copyright: {\textcopyright} 2021 IEEE.; 2021 IEEE International Conference on Real-Time Computing and Robotics, RCAR 2021 ; Conference date: 15-07-2021 Through 19-07-2021",

year = "2021",

month = jul,

day = "15",

doi = "10.1109/RCAR52367.2021.9517431",

language = "English",

series = "2021 IEEE International Conference on Real-Time Computing and Robotics, RCAR 2021",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

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booktitle = "2021 IEEE International Conference on Real-Time Computing and Robotics, RCAR 2021",

address = "United States",

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Duan, X, Jin, L, Li, C, He, R, Lai, Q & Ma, R 2021, Kinematic self-calibration of a 3-DOF parallel mechanism with ill-conditioned identification matrix. 在 2021 IEEE International Conference on Real-Time Computing and Robotics, RCAR 2021. 2021 IEEE International Conference on Real-Time Computing and Robotics, RCAR 2021, Institute of Electrical and Electronics Engineers Inc., 页码 314-318, 2021 IEEE International Conference on Real-Time Computing and Robotics, RCAR 2021, Xining, 中国, 15/07/21. https://doi.org/10.1109/RCAR52367.2021.9517431

Kinematic self-calibration of a 3-DOF parallel mechanism with ill-conditioned identification matrix. / Duan, Xingguang; Jin, Lixing; Li, Changsheng 等.
2021 IEEE International Conference on Real-Time Computing and Robotics, RCAR 2021. Institute of Electrical and Electronics Engineers Inc., 2021. 页码 314-318 (2021 IEEE International Conference on Real-Time Computing and Robotics, RCAR 2021).

科研成果: 书/报告/会议事项章节 › 会议稿件 › 同行评审

TY - GEN

T1 - Kinematic self-calibration of a 3-DOF parallel mechanism with ill-conditioned identification matrix

AU - Duan, Xingguang

AU - Jin, Lixing

AU - Li, Changsheng

AU - He, Rui

AU - Lai, Quanbin

AU - Ma, Rui

PY - 2021/7/15

Y1 - 2021/7/15

N2 - Kinematics calibration is an effective means to improve the accuracy of the mechanism. Parallel mechanisms with redundant actuation have potential for kinematic self-calibration. In this paper, the self-calibration algorithms of a parallel mechanism with 3-DOF are studied. The Jacobian matrix for self-calibration is ill-posed/ill-condition caused by multicollinearity between kinematics parameter, and the calculation with least square method diverges. Truncated singular value decomposition (TSVD), ridge regression (RR) and Liu estimation algorithm are utilized to address this problem, and the identification performances under different error parameters are compared.

AB - Kinematics calibration is an effective means to improve the accuracy of the mechanism. Parallel mechanisms with redundant actuation have potential for kinematic self-calibration. In this paper, the self-calibration algorithms of a parallel mechanism with 3-DOF are studied. The Jacobian matrix for self-calibration is ill-posed/ill-condition caused by multicollinearity between kinematics parameter, and the calculation with least square method diverges. Truncated singular value decomposition (TSVD), ridge regression (RR) and Liu estimation algorithm are utilized to address this problem, and the identification performances under different error parameters are compared.

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U2 - 10.1109/RCAR52367.2021.9517431

DO - 10.1109/RCAR52367.2021.9517431

M3 - Conference contribution

AN - SCOPUS:85115355070

T3 - 2021 IEEE International Conference on Real-Time Computing and Robotics, RCAR 2021

SP - 314

EP - 318

BT - 2021 IEEE International Conference on Real-Time Computing and Robotics, RCAR 2021

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 2021 IEEE International Conference on Real-Time Computing and Robotics, RCAR 2021

Y2 - 15 July 2021 through 19 July 2021

ER -

Duan X, Jin L, Li C, He R, Lai Q, Ma R. Kinematic self-calibration of a 3-DOF parallel mechanism with ill-conditioned identification matrix. 在 2021 IEEE International Conference on Real-Time Computing and Robotics, RCAR 2021. Institute of Electrical and Electronics Engineers Inc. 2021. 页码 314-318. (2021 IEEE International Conference on Real-Time Computing and Robotics, RCAR 2021). doi: 10.1109/RCAR52367.2021.9517431

Kinematic self-calibration of a 3-DOF parallel mechanism with ill-conditioned identification matrix

摘要

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