Intelligent Static Calibration of Industrial Robots using Artificial Bee Colony Algorithm

Abstract

This paper proposes an industrial robot calibration methodology using an artificial bee colony algorithm. Open loop industrial robot positions are usually calculated using joint angle readings and industrial robot forward kinematics, where feedback control systems are then use iteratively to improve performance. This can often be time consuming and risks unstable control, so the preference is to enable as accurate open loop control as possible. Industrial robot forward kinematics include Denavit-Hartenberg (DH) parameters. However, assembly and manufacturing tolerances may result in differences between actual and nominal DH parameters. To improve industrial robot positional accuracies, it is required to better estimate its DH parameters. A highly accurate laser tracker system provides the positional measurement required to perform calibration of the DH parameters. For this purpose, a Leica AT960-MR, a laser tracker which works based on interferometry principles, is used to provide end effector 3D position measurements. An artificial Bee colony algorithm is then used to improve the cost function associated with the forward kinematic error by estimating more accurate industrial robot DH parameters. The implementation results demonstrate that using calibrated industrial robot DH parameters, it is possible to improve the open loop positional accuracies of the robot compared to uncalibrated forward kinematics mean absolute error for test data from 75.4 $\mu$m to 60.1 $\mu$m (20.3% improvement).