Serial robots geometrical parameter identification using modified quantum behaved particle swarm optimization

Abstract

Knowledge of stringent value of the robot end-effector position is necessary in several industrial applications such as macroscopic structure measurement and assemblage. However, industrial robots cannot meet this challenge because of numerous errors. This paper presents a new method using quantum behaved particle swarm optimization (QPSO) to calibrate the robot geometrical parameters to improve the positioning accuracy of serial robots. Firstly, the errors of the axes are analysed, then the QPSO is used to calculate the errors. Experimental results show that the proposed method can effectively identify the robot geometrical parameters.