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An improved minimal error model for the robotic kinematic calibration based on the POE formula

Published online by Cambridge University Press:  20 September 2021

Ruiqing Luo Open the ORCID record for Ruiqing Luo [Opens in a new window] ,
Wenbin Gao ,
Qi Huang  and
Yi Zhang
Ruiqing Luo
Affiliation:
School of Mechanical Engineering, Anhui University of Technology, MA’Anshan, China Anhui Province Key Laboratory of Special Heavy Load Robot, MA’Anshan, China
Wenbin Gao*
Affiliation:
School of Mechanical Engineering, Anhui University of Technology, MA’Anshan, China Anhui Province Key Laboratory of Special Heavy Load Robot, MA’Anshan, China
Qi Huang
Affiliation:
School of Mechanical Engineering, Anhui University of Technology, MA’Anshan, China Anhui Province Key Laboratory of Special Heavy Load Robot, MA’Anshan, China
Yi Zhang
Affiliation:
State Key Laboratory of Robotics, Shenyang Institute of Automation, Chinese Academy of Sciences, Shenyang, China
*
*Corresponding author. E-mail: wenbingao@foxmail.com
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Summary

The conventional product of exponentials $\left(\rm POE\right)$ -based methods dissatisfy the parametric minimality for the kinematic calibration of serial robots due to overlooking the magnitude and pitch constraints. Thus, the minimal kinematic model is presented to solve this problem, which can be developed further. This paper puts forward an improved algorithm for the minimal parameter calibration. An actual kinematic model with the minimal parameters $\left(\rm MP\right)$ is constructed according to the geometric properties of actual joint twists in the auxiliary frames established on the basis of the nominal joint axes. Then, the initial pose error is defined in the tool coordinate frame, which is expressed as the exponential map of the twist, and all twist descriptions are unified, so as to give a unified kinematic model in mathematics. By differentiating the kinematic model, a minimal error model is derived in explicit form. Subsequently, we propose a novel parameter identification method, which identifies the orientation error and position error parameters separately by the iterative least-squares method and updates the MP uniformly. Finally, the simulations and experiments on the different serial robots are conducted to verify the correctness and effectiveness of the proposed algorithm. The simulation results show our calibration algorithm outperforms the existing ones in the accuracy aspect, and the experiment result shows that the absolute pose accuracy of the UR5 industrial robot is upgraded about 9 times under a statistics sense after the calibration.

Keywords

Kinematic calibrationProduct of exponentials (POE)Parametrically minimalIdentification
Type
Research Article
Information
Robotica , Volume 40 , Issue 5 , May 2022 , pp. 1607 - 1626
Copyright
© The Author(s), 2021. Published by Cambridge University Press

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