Accurate Calibration of Kinematic Parameters of a Robot Using a Laser Tracking System : Compensation of Non-Geometric Errors Using Neural Networks and Selection of Optimal Measuring Points Using Genetic Algorithm

Abstract

A laser tracking system is employed for measuring the robot arm's tip with high accuracy. The geometric parameters in the robot kinematic model are calibrated by minimizing errors between the measured positions and the predicted ones based on the model. The residual errors caused by non-geometric parameters are further reduced by using neural networks, realizing the high positioning accuracy of sub-millimeter order. To speed up the calibration process, the smaller number of measuring points is preferable. Optimal measuring points, which realize high positioning accuracy with small point number, are selected using genetic algorithm (GA).