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

Author:

Xiao Zhengming12,Duan Junjie1,Wu Xing3,Kang Zhenhui1

Affiliation:

1. Faculty of Mechanical and Electrical Engineering, Kunming University of Science and Technology, Kunming, China

2. Key Laboratory of Yunnan Advanced Equipment Intelligent Manufacturing Technology, Kunming, China

3. Yunnan Vocational College of Mechanical and Electrical Technology, Kunming, China

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.

Funder

the Special Project for International Science and Technology Cooperation of Key R&D Program of Yunnan Province

the Faceted Project of Basic Research Program of Yunnan Province

National Natural Science Foundation of China

Publisher

SAGE Publications

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