The Method of Kinematic Parameter Calibration for a Robot Based on the K-PSO Algorithm
Aiming at the error problem caused by robot movement,a robot kinematic parameter calibration method based on the K-PSO algorithm is proposed.This method can be used to compensate for errors in ro-bot parameter calibration and greatly improve the robot's movement accuracy.The K-PSO algorithm com-bines the ideas of K-means clustering and particle swarm optimization.Firstly,the K-means clustering algo-rithm is used to group the initial particles of the robot's kinematic parameters,then the parameters are opti-mized through an improved particle swarm optimization algorithm.Experimental results show that the im-proved K-PSO method can effectively reduce computational complexity,and has faster convergence speed and higher parameter estimation accuracy.This method holds significant implications for the precise control and motion planning of robots.
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