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Joint Calibration Method for Robot Measurement Systems

Robot measurement systems with a binocular planar structured light camera (3D camera) installed on a robot end-effector are often used to measure workpieces’ shapes and positions. However, the measurement accuracy is jointly influenced by the robot kinematics, camera-to-robot installation, and 3D ca...

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Autores principales: Wu, Lei, Zang, Xizhe, Ding, Guanwen, Wang, Chao, Zhang, Xuehe, Liu, Yubin, Zhao, Jie
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10490635/
https://www.ncbi.nlm.nih.gov/pubmed/37687903
http://dx.doi.org/10.3390/s23177447
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author Wu, Lei
Zang, Xizhe
Ding, Guanwen
Wang, Chao
Zhang, Xuehe
Liu, Yubin
Zhao, Jie
author_facet Wu, Lei
Zang, Xizhe
Ding, Guanwen
Wang, Chao
Zhang, Xuehe
Liu, Yubin
Zhao, Jie
author_sort Wu, Lei
collection PubMed
description Robot measurement systems with a binocular planar structured light camera (3D camera) installed on a robot end-effector are often used to measure workpieces’ shapes and positions. However, the measurement accuracy is jointly influenced by the robot kinematics, camera-to-robot installation, and 3D camera measurement errors. Incomplete calibration of these errors can result in inaccurate measurements. This paper proposes a joint calibration method considering these three error types to achieve overall calibration. In this method, error models of the robot kinematics and camera-to-robot installation are formulated using Lie algebra. Then, a pillow error model is proposed for the 3D camera based on its error distribution and measurement principle. These error models are combined to construct a joint model based on homogeneous transformation. Finally, the calibration problem is transformed into a stepwise optimization problem that minimizes the sum of the relative position error between the calibrator and robot, and analytical solutions for the calibration parameters are derived. Simulation and experiment results demonstrate that the joint calibration method effectively improves the measurement accuracy, reducing the mean positioning error from over 2.5228 mm to 0.2629 mm and the mean distance error from over 0.1488 mm to 0.1232 mm.
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spelling pubmed-104906352023-09-09 Joint Calibration Method for Robot Measurement Systems Wu, Lei Zang, Xizhe Ding, Guanwen Wang, Chao Zhang, Xuehe Liu, Yubin Zhao, Jie Sensors (Basel) Article Robot measurement systems with a binocular planar structured light camera (3D camera) installed on a robot end-effector are often used to measure workpieces’ shapes and positions. However, the measurement accuracy is jointly influenced by the robot kinematics, camera-to-robot installation, and 3D camera measurement errors. Incomplete calibration of these errors can result in inaccurate measurements. This paper proposes a joint calibration method considering these three error types to achieve overall calibration. In this method, error models of the robot kinematics and camera-to-robot installation are formulated using Lie algebra. Then, a pillow error model is proposed for the 3D camera based on its error distribution and measurement principle. These error models are combined to construct a joint model based on homogeneous transformation. Finally, the calibration problem is transformed into a stepwise optimization problem that minimizes the sum of the relative position error between the calibrator and robot, and analytical solutions for the calibration parameters are derived. Simulation and experiment results demonstrate that the joint calibration method effectively improves the measurement accuracy, reducing the mean positioning error from over 2.5228 mm to 0.2629 mm and the mean distance error from over 0.1488 mm to 0.1232 mm. MDPI 2023-08-26 /pmc/articles/PMC10490635/ /pubmed/37687903 http://dx.doi.org/10.3390/s23177447 Text en © 2023 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Wu, Lei
Zang, Xizhe
Ding, Guanwen
Wang, Chao
Zhang, Xuehe
Liu, Yubin
Zhao, Jie
Joint Calibration Method for Robot Measurement Systems
title Joint Calibration Method for Robot Measurement Systems
title_full Joint Calibration Method for Robot Measurement Systems
title_fullStr Joint Calibration Method for Robot Measurement Systems
title_full_unstemmed Joint Calibration Method for Robot Measurement Systems
title_short Joint Calibration Method for Robot Measurement Systems
title_sort joint calibration method for robot measurement systems
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10490635/
https://www.ncbi.nlm.nih.gov/pubmed/37687903
http://dx.doi.org/10.3390/s23177447
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