Evaluation and prediction method of robot pose repeatability based on statistical distance

Abstract

Pose repeatability is one of the most important performance specifications of robots, and its evaluation and prediction methods are of great significance to give full play to the precision characteristics of robot. In this paper, a pose repeatability evaluation method based on statistical distance and spatial probability ellipsoid is proposed, which can accurately and effectively describe the coupling effect between repeatability of various dimensionalities. On this basis, a prediction model of pose repeatability based on equivalent system is proposed. In this model, the pose repeatability of the end-effector is considered to be generated only by the equivalent repeatability of the actuated joint, and the latter is described as a function of the ideal actuated joint variables, which can accurately describe the variation of the pose repeatability caused by the uncertainties of the robot system in the whole workspace. Simulation and experimental study on a 6-DOF parallel robot are carried out to illustrate the effectiveness of the proposed approach.