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| Research on Robot Kinematics Parameter Calibration Based on Particle Swarm Optimization |
| CHEN Xiang-jun1,3,ZHAO Zhi-fang2,Ren Guo-ying2,3,LI Da-chao1,BAN Zhao3,4 |
1. State key laboratory of precision measurement technology and instruments, Tianjin university,Tianjin 300072,China
2. Xinjiang Uygur Autonomous Region Research Institute of Measurement and Testing, Urumqi,Xinjiang 830011, China
3. National Institute of Metrology,Beijing 100029,China
4. College of Mechanical and Electrical Engineering,China Jiliang University, Hangzhou, Zhejiang 310018,China |
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Abstract In order to improve the absolute positioning accuracy of robot end, a calibration method of robot kinematic geometric parameters based on particle swarm optimization (PSO) was proposed to identify and compensate the parameter errors of industrial robots. First, in order to avoid the singularity when two adjacent axes of the manipulator are parallel, MDH parameter method was adopted to establish the error model. Secondly, in order to define the measurement data on the same coordinate axis, the coordinate conversion method of synchronous calibration of robot orientation and hand-eye relationship combined with model precision compensation was used. Then particle swarm optimization (PSO) algorithm was used to identify the model geometric parameter error. Through the simulation, experimental calculation and calibration of ABB industrial robots, the average absolute positioning accuracy of robots was improved by 66.9%. The results showed that the calibration algorithm can effectively identify the model parameter errors of the robot and improve the absolute positioning accuracy after compensating the model parameters of the robot.
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2020, Vol. 41 
