An Efficient Robot Payload Identification Method Based on Decomposed Motion Experimental Approach

Abstract

For most industrial/collaborative robot applications of model-based control, an accurate dynamic model is crucial to achieve good performance of the controller. Depending on the needs of different tasks, robots are often equipped with a variety of end effectors with various dynamic parameters (mass, center of mass and inertia), which could make the overall dynamics of the robot uncertain. This paper aims to identify the dynamic parameters of robot payload in its application by developing a new method with a 4-step motion, where only one joint needs to move in each step. Thanks to this particular motion with single joint, the robot dynamics can be decoupled and only the data of three joints which near the end-effector need to be collected. For each motion step, the adoption of a simplified dynamic model with fewer payload parameters is facilitated by the design of a special initial position and trajectory for a single joint, so that the impact of parameter on the accuracy of identification is significantly reduced compared with existing methods where multiple parameters are excited at the same time. Furthermore, a solving method of payload parameters based on the least squares method. The experimental results with a 6R industrial robot show the effectiveness of the proposed method for identifying different kinds of unknown payloads.