Global Identification of Joint Drive Gains and Dynamic Parameters of Robots

Abstract

Offline robot dynamic identification methods are based on the use of the inverse dynamic identification model (IDIM), which calculates the joint forces/torques that are linear in relation to the dynamic parameters, and on the use of linear least squares technique to calculate the parameters (IDIMLS technique). The joint forces/torques are calculated as the product of the known control signal (the input reference of the motor current loop) by the joint drive gains. Then it is essential to get accurate values of joint drive gains to get accurate estimation of the motor torques and accurate identification of dynamic parameters. The previous works proposed to identify the gain of one joint at a time using data of each joint separately. This is a sequential procedure which accumulates errors from step to step. To overcome this drawback, this paper proposes a global identification of the drive gains of all joints and the dynamic parameters of all links. They are calculated altogether in a single step using all the data of all joints at the same time. The method is based on the total least squares solution of an overdetermined linear system obtained with the inverse dynamic model calculated with available input reference of the motor current loop and joint position sampled data while the robot is tracking some reference trajectories without load on the robot and some trajectories with a known payload fixed on the robot. The method is experimentally validated on an industrial Stأ¤ubli TX40 robot.