An Experimental Robot Load Identification Method for Industrial Application

Abstract

In this paper, we discuss a new experimental robot load identification method that is used in industry. The method is based on periodic robot excitation and the maximum likelihood estimation of the parameters, techniques adopted from Swevers et al. (1997 IEEE Transactions on Robotics and Automation 13(5):730—740). This method provides: (1) accurate estimates of the robot load inertial parameters; and (2) accurate actuator torque predictions. These are both essential for the acceptance of the results in an industrial environment. The key element to the success of this method is the comprehensiveness of the applied model, which includes, besides the dynamics resulting from the robot load and motor inertia, the coupling between the actuator torques, the mechanical losses in the motors and the efficiency of the transmissions. Accurate estimates of the robot link and motor inertial parameters, which can be considered identical for all robots of the same type, are obtained from separate experiments (see Swevers et al.), and used as a priori knowledge for the robot load identification. We present experimental results on a KUKA industrial robot equipped with a calibrated test load.