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Kinematic calibration and accuracy study of a 5-degrees-of-freedom hybrid polishing robot

Published online by Cambridge University Press:  17 October 2025

Bo Sun Open the ORCID record for Bo Sun [Opens in a new window] ,
Mingyang Qin ,
Yaolin Jiang  and
Gang Cheng Open the ORCID record for Gang Cheng [Opens in a new window]
Bo Sun
Affiliation:
School of Mechatronic Engineering, China University of Mining and Technology, Xuzhou, China
Mingyang Qin
Affiliation:
School of Mechatronic Engineering, China University of Mining and Technology, Xuzhou, China
Yaolin Jiang
Affiliation:
School of Mechatronic Engineering, China University of Mining and Technology, Xuzhou, China
Gang Cheng*
Affiliation:
School of Mechatronic Engineering, China University of Mining and Technology, Xuzhou, China
*
Corresponding author: Gang Cheng; Email: chg@cumt.edu.cn
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Abstract

An improved identification algorithm is adopted to calibrate the kinematic parameters of the serial-parallel robot, which improves the motion accuracy of the end-effector. Firstly, a kinematic model of the serial-parallel robot is constructed based on the closed-loop vector method. Secondly, a kinematic error model is established by combining geometric error analysis with the vector differential method. Then, with the effective separation of compensable and non-compensable error sources, an identification model of kinematic parameters is constructed. Finally, an improved pivot element weighted iterative algorithm is used to identify the geometric error parameters. Through actual pose measurement, MATLAB is used to simulate the calibration process. The simulation and experimental results show that after kinematic calibration, compared with the traditional least squares method, the improved identification algorithm can significantly reduce the end-effector pose error of the serial-parallel robot, thus effectively improving the motion accuracy of the end-effector.

Keywords

hybrid polishing roboterror modelcalibration modelerror analysismotion accuracy

Information

Type
Research Article
Information
Robotica , First View , pp. 1 - 19
Copyright
© The Author(s), 2025. Published by Cambridge University Press

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