Variable Stiffness Identification and Configuration Optimization of Industrial Robots for Machining Tasks
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...
| Main Authors: | , , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
SpringerOpen
2022-09-01
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| Series: | Chinese Journal of Mechanical Engineering |
| Subjects: | |
| Online Access: | https://doi.org/10.1186/s10033-022-00778-1 |
| _version_ | 1811273680919986176 |
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| author | Jiachen Jiao Wei Tian Lin Zhang Bo Li Junshan Hu Yufei Li Dawei Li Jianlong Zhang |
| author_facet | Jiachen Jiao Wei Tian Lin Zhang Bo Li Junshan Hu Yufei Li Dawei Li Jianlong Zhang |
| author_sort | Jiachen Jiao |
| collection | DOAJ |
| description | 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. |
| first_indexed | 2024-04-12T23:03:38Z |
| format | Article |
| id | doaj.art-92dfd34364324513994b87a09483fd54 |
| institution | Directory Open Access Journal |
| issn | 1000-9345 2192-8258 |
| language | English |
| last_indexed | 2024-04-12T23:03:38Z |
| publishDate | 2022-09-01 |
| publisher | SpringerOpen |
| record_format | Article |
| series | Chinese Journal of Mechanical Engineering |
| spelling | doaj.art-92dfd34364324513994b87a09483fd542022-12-22T03:12:59ZengSpringerOpenChinese Journal of Mechanical Engineering1000-93452192-82582022-09-0135111610.1186/s10033-022-00778-1Variable Stiffness Identification and Configuration Optimization of Industrial Robots for Machining TasksJiachen Jiao0Wei Tian1Lin Zhang2Bo Li3Junshan Hu4Yufei Li5Dawei Li6Jianlong Zhang7Nanjing University of Aeronautics and AstronauticsNanjing University of Aeronautics and AstronauticsNanjing University of Aeronautics and AstronauticsNanjing University of Aeronautics and AstronauticsNanjing University of Aeronautics and AstronauticsNanjing University of Aeronautics and AstronauticsBeijing Institute of Mechanical EquipmentBeijing Institute of Space Launch TechnologyAbstract 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.https://doi.org/10.1186/s10033-022-00778-1Industrial robotSpace griddingVariable stiffness identificationConfiguration optimizationSmooth processing |
| spellingShingle | 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 Chinese Journal of Mechanical Engineering Industrial robot Space gridding Variable stiffness identification Configuration optimization Smooth processing |
| title | Variable Stiffness Identification and Configuration Optimization of Industrial Robots for Machining Tasks |
| title_full | Variable Stiffness Identification and Configuration Optimization of Industrial Robots for Machining Tasks |
| title_fullStr | Variable Stiffness Identification and Configuration Optimization of Industrial Robots for Machining Tasks |
| title_full_unstemmed | Variable Stiffness Identification and Configuration Optimization of Industrial Robots for Machining Tasks |
| title_short | Variable Stiffness Identification and Configuration Optimization of Industrial Robots for Machining Tasks |
| title_sort | variable stiffness identification and configuration optimization of industrial robots for machining tasks |
| topic | Industrial robot Space gridding Variable stiffness identification Configuration optimization Smooth processing |
| url | https://doi.org/10.1186/s10033-022-00778-1 |
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