Dynamic Parameter Identification of Six-axis Industrial Robot Based on Improved Genetic Algorithm

Focusing on the problems that the traditional genetic algorithm optimization excitation trajectory cannot meet the constraints in the robot parameter identification, a dynamic parameter identification method based on the improved genetic algorithm is proposed. Firstly, a linearized industrial robot...

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Bibliographic Details
Published in2022 12th International Conference on CYBER Technology in Automation, Control, and Intelligent Systems (CYBER) pp. 614 - 619
Main Authors Li, Yan, Ni, Dawei, Wei, Chengyu, Lu, Zengpeng, Zhang, Zhenguo, Liu, Keping
Format Conference Proceeding
LanguageEnglish
Published IEEE 27.07.2022
Subjects
dynamic parameter identification
excitation trajectory
Heuristic algorithms
improved genetic algorithm
industrial robot
Intelligent systems
Parameter estimation
Robot sensing systems
Sensors
Service robots
Trajectory
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Summary:Focusing on the problems that the traditional genetic algorithm optimization excitation trajectory cannot meet the constraints in the robot parameter identification, a dynamic parameter identification method based on the improved genetic algorithm is proposed. Firstly, a linearized industrial robot dynamic model is built. Secondly, the excitation trajectory is obtained by optimizing the improved genetic algorithm. Finally, calculate the robot dynamic parameters by the least square method. The experimental results show that the optimal excitation trajectory obtained by this method can meet the constraints, shorten the optimization time and effectively improve the efficiency and effect of dynamic parameter identification.
ISSN:2642-6633
DOI:10.1109/CYBER55403.2022.9907327