Chinese Journal of Mechanical Engineering >

2022 , Vol. 35 >Issue 5: 115 - 115

DOI: https://doi.org/10.1186/s10033-022-00778-1

Mechanism and Robotics

Variable Stiffness Identification and Configuration Optimization of Industrial Robots for Machining Tasks

  • Jiachen Jiao ,
  • Wei Tian ,
  • Lin Zhang ,
  • Bo Li ,
  • Junshan Hu ,
  • Yufei Li ,
  • Dawei Li ,
  • Jianlong Zhang
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  • 1. Nanjing University of Aeronautics and Astronautics, Nanjing, 210016, China;
    2. Beijing Institute of Space Launch Technology, Beijing, 100076, China;
    3. Beijing Institute of Mechanical Equipment, Beijing, 100854, China

收稿日期: 2020-07-14

  修回日期: 2021-04-15

  网络出版日期: 2023-04-24

基金资助

Supported by National Natural Science Foundation of China (Grant No. 51875287), National Defense Basic Scientific Research Program of China (Grant No. JCKY2018605C002) and Jiangsu Provincial Natural Science Foundation of China (Grant No. BK20190417).

收起

Variable Stiffness Identification and Configuration Optimization of Industrial Robots for Machining Tasks

  • Jiachen Jiao ,
  • Wei Tian ,
  • Lin Zhang ,
  • Bo Li ,
  • Junshan Hu ,
  • Yufei Li ,
  • Dawei Li ,
  • Jianlong Zhang
Expand
  • 1. Nanjing University of Aeronautics and Astronautics, Nanjing, 210016, China;
    2. Beijing Institute of Space Launch Technology, Beijing, 100076, China;
    3. Beijing Institute of Mechanical Equipment, Beijing, 100854, China

Received date: 2020-07-14

  Revised date: 2021-04-15

  Online published: 2023-04-24

Supported by

Supported by National Natural Science Foundation of China (Grant No. 51875287), National Defense Basic Scientific Research Program of China (Grant No. JCKY2018605C002) and Jiangsu Provincial Natural Science Foundation of China (Grant No. BK20190417).

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摘要

Industrial robots are increasingly being used in machining tasks because of their high flexibility and intelligence. However, the low structural stiffness of a robot significantly affects its positional accuracy and the machining quality of its operation equipment. Studying robot stiffness characteristics and optimization methods is an effective method of improving the stiffness performance of a robot. Accordingly, aiming at the poor accuracy of stiffness modeling caused by approximating the stiffness of each joint as a constant, a variable stiffness identification method is proposed based on space gridding. Subsequently, a task-oriented axial stiffness evaluation index is proposed to quantitatively assess the stiffness performance in the machining direction. In addition, by analyzing the redundant kinematic characteristics of the robot machining system, a configuration optimization method is further developed to maximize the index. For numerous points or trajectory-processing tasks, a configuration smoothing strategy is proposed to rapidly acquire optimized configurations. Finally, experiments on a KR500 robot were conducted to verify the feasibility and validity of the proposed stiffness identification and configuration optimization methods.

关键词： Industrial robot; Space gridding; Variable stiffness identification; Configuration optimization; Smooth processing

本文引用格式

Jiachen Jiao , Wei Tian , Lin Zhang , Bo Li , Junshan Hu , Yufei Li , Dawei Li , Jianlong Zhang . Variable Stiffness Identification and Configuration Optimization of Industrial Robots for Machining Tasks[J]. Chinese Journal of Mechanical Engineering, 2022 , 35(5) : 115 -115 . DOI: 10.1186/s10033-022-00778-1

Abstract

Industrial robots are increasingly being used in machining tasks because of their high flexibility and intelligence. However, the low structural stiffness of a robot significantly affects its positional accuracy and the machining quality of its operation equipment. Studying robot stiffness characteristics and optimization methods is an effective method of improving the stiffness performance of a robot. Accordingly, aiming at the poor accuracy of stiffness modeling caused by approximating the stiffness of each joint as a constant, a variable stiffness identification method is proposed based on space gridding. Subsequently, a task-oriented axial stiffness evaluation index is proposed to quantitatively assess the stiffness performance in the machining direction. In addition, by analyzing the redundant kinematic characteristics of the robot machining system, a configuration optimization method is further developed to maximize the index. For numerous points or trajectory-processing tasks, a configuration smoothing strategy is proposed to rapidly acquire optimized configurations. Finally, experiments on a KR500 robot were conducted to verify the feasibility and validity of the proposed stiffness identification and configuration optimization methods.

Key words： Industrial robot; Space gridding; Variable stiffness identification; Configuration optimization; Smooth processing

参考文献

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