A stochastic ellipsoid approach to repeatability modelisation of industrial manipulator robots

Abstract

Most industrial manipulator robots are used in assembly tasks. Their manufacturers use repeatability parameters to show their effectiveness. IS09283 standard details the process of measuring repeatability. As loads, speed and other various factors affect repeatability, a high number of experimental trials are needed to obtain significant values. Moreover, repeatability is also affected by the location of the robot's endpoint in its workspace. In this paper, we construct a stochastic model to evaluate repeatability in the whole workspace of the robot. For this, we only need to determine the robot geometry and sensor sensitivity. Consequently, it is possible with only a few experimental measures to map robot repeatability and obtain relevant information about the spatial error distribution around the points' mean position. This method has been applied to a SCARA robot and has led to specific mapping. Experimental results have been compared with the results of the stochastic ellipsoid model.