Machine vision system for the automatic identification of robot kinematic parameters

Abstract

This paper presents an efficient, noncontact measurement technique for the automatic identification of the real kinematic parameters of an industrial robot. The technique is based on least-squares analysis and on the Hayati and Mirmirani kinematic modeling convention for closed kinematic chains. The measurement system consists of a single camera mounted on the robot's wrist. The camera measures position and orientation of a passive target in six degrees of freedom. Target position is evaluated by applying least-squares analysis on an overdetermined system of equations based on the quaternion representation of the finite rotation formula. To enhance the accuracy of the measurement, a variety of image processing functions including subpixel interpolation are applied.