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A New Prediction Method of Displacement Errors Caused by Low Stiffness for Industrial Robot

This paper presents a new method, a fast prediction method based on the Cartesian stiffness model and equivalent spring stiffness (FPM-CSES), to calculate displacement errors of deformation caused by low stiffness for industrial robot. First, the Cartesian stiffness model based on the Jacobian matri...

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Detalles Bibliográficos
Autores principales: He, Zhenya, Song, Mingjing, Zhang, Xianmin, Huang, Guojian
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9412293/
https://www.ncbi.nlm.nih.gov/pubmed/36015723
http://dx.doi.org/10.3390/s22165963
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author He, Zhenya
Song, Mingjing
Zhang, Xianmin
Huang, Guojian
author_facet He, Zhenya
Song, Mingjing
Zhang, Xianmin
Huang, Guojian
author_sort He, Zhenya
collection PubMed
description This paper presents a new method, a fast prediction method based on the Cartesian stiffness model and equivalent spring stiffness (FPM-CSES), to calculate displacement errors of deformation caused by low stiffness for industrial robot. First, the Cartesian stiffness model based on the Jacobian matrix was established for a robot, and then the displacement error model of deformations caused by external force was established based on Cartesian stiffness. Second, the transmission system of the robot’s joint was analyzed, and an equivalent method for joint stiffness was presented based on a series spring system. Meanwhile, the stiffness of the key components including the servo motor, harmonic reducer, and timing belt was deduced in detail. Finally, a compared simulation and a measurement experiment were conducted on a 6-joint series robot. It was found that the FPM-CSES could calculate any configuration among the robot’s workspace. Compared with the finite element analysis (FEA) method, the presented method is feasible and more efficient. The experimental results showed that the prediction accuracy of the FPM-CSES is rather high, with an average rate of more than 83.72%. Hence, the prediction method presented in this study is simple, fast, and reliable, and could be used to predict and analyze the displacement errors caused by the cutting force, and provide the basis for trajectory planning and error compensation, enhancing the robot’s machining performance.
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spelling pubmed-94122932022-08-27 A New Prediction Method of Displacement Errors Caused by Low Stiffness for Industrial Robot He, Zhenya Song, Mingjing Zhang, Xianmin Huang, Guojian Sensors (Basel) Article This paper presents a new method, a fast prediction method based on the Cartesian stiffness model and equivalent spring stiffness (FPM-CSES), to calculate displacement errors of deformation caused by low stiffness for industrial robot. First, the Cartesian stiffness model based on the Jacobian matrix was established for a robot, and then the displacement error model of deformations caused by external force was established based on Cartesian stiffness. Second, the transmission system of the robot’s joint was analyzed, and an equivalent method for joint stiffness was presented based on a series spring system. Meanwhile, the stiffness of the key components including the servo motor, harmonic reducer, and timing belt was deduced in detail. Finally, a compared simulation and a measurement experiment were conducted on a 6-joint series robot. It was found that the FPM-CSES could calculate any configuration among the robot’s workspace. Compared with the finite element analysis (FEA) method, the presented method is feasible and more efficient. The experimental results showed that the prediction accuracy of the FPM-CSES is rather high, with an average rate of more than 83.72%. Hence, the prediction method presented in this study is simple, fast, and reliable, and could be used to predict and analyze the displacement errors caused by the cutting force, and provide the basis for trajectory planning and error compensation, enhancing the robot’s machining performance. MDPI 2022-08-09 /pmc/articles/PMC9412293/ /pubmed/36015723 http://dx.doi.org/10.3390/s22165963 Text en © 2022 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
He, Zhenya
Song, Mingjing
Zhang, Xianmin
Huang, Guojian
A New Prediction Method of Displacement Errors Caused by Low Stiffness for Industrial Robot
title A New Prediction Method of Displacement Errors Caused by Low Stiffness for Industrial Robot
title_full A New Prediction Method of Displacement Errors Caused by Low Stiffness for Industrial Robot
title_fullStr A New Prediction Method of Displacement Errors Caused by Low Stiffness for Industrial Robot
title_full_unstemmed A New Prediction Method of Displacement Errors Caused by Low Stiffness for Industrial Robot
title_short A New Prediction Method of Displacement Errors Caused by Low Stiffness for Industrial Robot
title_sort new prediction method of displacement errors caused by low stiffness for industrial robot
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9412293/
https://www.ncbi.nlm.nih.gov/pubmed/36015723
http://dx.doi.org/10.3390/s22165963
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