Arm signature identification

Abstract

The positioning accuracy of commercially-available industrial robotic manipulators depends upon a kinematic model which describes the robot geometry in a parametric form. Manufacturing errors in machining and assembly of manipulators lead to discrepancies between the design parameters and the physical structure. Improving the kinematic performance thus requires identification of the actual kinematic parameters of each individual robot. This identification of the individual kinematic parameters is called the arm signature which is then incorporated into the manipulator's controller to improve positional accuracy. In this paper, an approach, based on a new parametric model of the kinematics, is introduced for arm signature identification. The S-Model utilizes 6.n parameters to describe the robot geometry and offers advantages for identification by decomposing the parameters into individually identified subsets. The S-Model parameters are then mapped into the equivalent Denavit-Hartenberg parameters for implementation into the controller. The S-Model arm signature identification algorithm can be implemented with relatively simple sensors and improves accuracy through statistical averaging. This algorithm has been implemented with an external ultrasonic range sensor to measure robot end-effector positions. Experimental results of arm signature identification of seven Unimation/Westinghouse Puma 560 robots demonstrated an average reduction in positioning error by a factor of 5-10 for a spectrum of representative test tasks.