Improving the Positional Accuracy of Industrial Robots by Forward Kinematic Calibration using Laser Tracker System

Abstract

Precision object handling and manipulation require precise positioning of industrial robots. The common practice to perform end effector positioning is to use joint angle readings and industrial robot forward kinematics. However, forward kinematics of the robot rely on its DH parameter values which include uncertainties. Sources of uncertainty associated with robot forward kinematics include mechanical wear, manufacturing, assembly tolerances, and robot dimensional measurement errors. It is therefore highly required to increase the precision of DH parameter values. In this paper, we use heuristic optimization approaches to perform industrial robot DH parameter calibration. To perform this task, a highly accurate laser tracker system, Leica AT960-MR is utilized. The precision of this non-contact metrology device is less than 3μm/m and therefore it can be easily used to calibrate industrial robots with precision of 0.1mm. Heuristic optimization approaches such as genetic algorithm, particle swarm optimization, and differential evolution are used to perform the calibration using laser tracker position data as their target values. It is observed that using the proposed approach, the accuracy of industrial robot FKs in terms of mean absolute errors of static and near-static motion over all three position dimensions decreases from its measured value 66.5μm to 51.6μm (more than 22.4% improvement).