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Optimization of stiffness performance of six-axis industrial robots based on posture stiffness evaluation index.

Authors :
Xiao, Zhengming
Duan, Junjie
Wu, Xing
Kang, Zhenhui
Source :
Proceedings of the Institution of Mechanical Engineers, Part C: Journal of Mechanical Engineering Science (Sage Publications, Ltd.); Aug2024, Vol. 238 Issue 16, p8357-8365, 9p
Publication Year :
2024

Abstract

Aiming at the problem that the stiffness performance of industrial robots depends on the posture, a method to improve the stiffness performance by optimizing the robot posture is proposed based on the robot posture stiffness evaluation index. The robot joint stiffness identification model is established by using the principle of virtual work and Jacobi matrix, and the stiffness values of six joints are obtained by least-squares. On the basis of revealing the mapping relationship between robot joints and end, the robot end flexibility ellipsoid is obtained, and the volume of the end flexibility ellipsoid is utilized as the global stiffness coefficient of the robot, so as to obtain the robot posture stiffness evaluation index. According to the posture stiffness evaluation index, the robot posture optimization model is established, and the optimized posture is obtained by using genetic algorithm. Taking the QJR6-1 robot as the experimental object, under the maximum load, the deformation of the robot end center is reduced from 0.6238 to 0.3984 mm, which is 36.13%, and the deformation of the end is greatly reduced compared with that before the optimization, which indicates that the robot's stiffness is improved after the posture optimization, and it verifies the feasibility of the optimization model, and provides a reference to improve the stiffness performance of industrial robots further. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
09544062
Volume :
238
Issue :
16
Database :
Complementary Index
Journal :
Proceedings of the Institution of Mechanical Engineers, Part C: Journal of Mechanical Engineering Science (Sage Publications, Ltd.)
Publication Type :
Academic Journal
Accession number :
179022332
Full Text :
https://doi.org/10.1177/09544062241238800