Optimization Study of Excitation Trajectories for Dynamic Parameter Identification
In addressing the issue of identifying dynamic parameters for robotic arms, a trajectory optimization method was proposed using an improved snake optimization algorithm. This method was innovatively built upon the conventional snake optimization algorithm by introducing adaptive adjustment operators...
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| Format: | Article |
| Language: | zho |
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Editorial Office of Journal of Mechanical Transmission
2024-11-01
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| Series: | Jixie chuandong |
| Subjects: | |
| Online Access: | http://www.jxcd.net.cn/thesisDetails#10.16578/j.issn.1004.2539.2024.11.006 |
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| _version_ | 1841546881192165376 |
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| author | Yang Zhonghua Yu Jinghu Yu Zhe Zhou Jiaquan |
| author_facet | Yang Zhonghua Yu Jinghu Yu Zhe Zhou Jiaquan |
| author_sort | Yang Zhonghua |
| collection | DOAJ |
| description | In addressing the issue of identifying dynamic parameters for robotic arms, a trajectory optimization method was proposed using an improved snake optimization algorithm. This method was innovatively built upon the conventional snake optimization algorithm by introducing adaptive adjustment operators in place of fixed coefficients. This adaptation enhanced the global search capability and convergence speed of the snake optimization algorithm. The improved snake optimization algorithm was applied to the optimization design of excitation trajectories in the process of robotic arm dynamic parameter identification. The iterative reweighted least squares algorithm was employed as the parameter identification technique. In the experimental validation phase, a six-degree-of-freedom collaborative robot was chosen as the verification subject. The results demonstrate that, in comparison to conventional excitation trajectory design algorithms, the root mean square deviation of joint torques for the first three joints of the robotic arm decreases by 20.96%, while the root mean square deviation of joint torques for all six joints decreases by 23.58%. This verifies the effectiveness of applying the improved snake optimization algorithm to excitation trajectory optimization design, leading to enhanced accuracy in the dynamic parameter identification. |
| format | Article |
| id | doaj-art-350c6de67dba4bbf85829f767bb8a71c |
| institution | Kabale University |
| issn | 1004-2539 |
| language | zho |
| publishDate | 2024-11-01 |
| publisher | Editorial Office of Journal of Mechanical Transmission |
| record_format | Article |
| series | Jixie chuandong |
| spelling | doaj-art-350c6de67dba4bbf85829f767bb8a71c2025-01-10T15:01:50ZzhoEditorial Office of Journal of Mechanical TransmissionJixie chuandong1004-25392024-11-0148374777638942Optimization Study of Excitation Trajectories for Dynamic Parameter IdentificationYang ZhonghuaYu JinghuYu ZheZhou JiaquanIn addressing the issue of identifying dynamic parameters for robotic arms, a trajectory optimization method was proposed using an improved snake optimization algorithm. This method was innovatively built upon the conventional snake optimization algorithm by introducing adaptive adjustment operators in place of fixed coefficients. This adaptation enhanced the global search capability and convergence speed of the snake optimization algorithm. The improved snake optimization algorithm was applied to the optimization design of excitation trajectories in the process of robotic arm dynamic parameter identification. The iterative reweighted least squares algorithm was employed as the parameter identification technique. In the experimental validation phase, a six-degree-of-freedom collaborative robot was chosen as the verification subject. The results demonstrate that, in comparison to conventional excitation trajectory design algorithms, the root mean square deviation of joint torques for the first three joints of the robotic arm decreases by 20.96%, while the root mean square deviation of joint torques for all six joints decreases by 23.58%. This verifies the effectiveness of applying the improved snake optimization algorithm to excitation trajectory optimization design, leading to enhanced accuracy in the dynamic parameter identification.http://www.jxcd.net.cn/thesisDetails#10.16578/j.issn.1004.2539.2024.11.006Collaborative robotDynamic modelImproved snake optimization algorithmAdaptive operatorParameter identification |
| spellingShingle | Yang Zhonghua Yu Jinghu Yu Zhe Zhou Jiaquan Optimization Study of Excitation Trajectories for Dynamic Parameter Identification Jixie chuandong Collaborative robot Dynamic model Improved snake optimization algorithm Adaptive operator Parameter identification |
| title | Optimization Study of Excitation Trajectories for Dynamic Parameter Identification |
| title_full | Optimization Study of Excitation Trajectories for Dynamic Parameter Identification |
| title_fullStr | Optimization Study of Excitation Trajectories for Dynamic Parameter Identification |
| title_full_unstemmed | Optimization Study of Excitation Trajectories for Dynamic Parameter Identification |
| title_short | Optimization Study of Excitation Trajectories for Dynamic Parameter Identification |
| title_sort | optimization study of excitation trajectories for dynamic parameter identification |
| topic | Collaborative robot Dynamic model Improved snake optimization algorithm Adaptive operator Parameter identification |
| url | http://www.jxcd.net.cn/thesisDetails#10.16578/j.issn.1004.2539.2024.11.006 |
| work_keys_str_mv | AT yangzhonghua optimizationstudyofexcitationtrajectoriesfordynamicparameteridentification AT yujinghu optimizationstudyofexcitationtrajectoriesfordynamicparameteridentification AT yuzhe optimizationstudyofexcitationtrajectoriesfordynamicparameteridentification AT zhoujiaquan optimizationstudyofexcitationtrajectoriesfordynamicparameteridentification |