Stiffness Identification for Serial Robot Manipulator Based on Uncertainty Approach

Stiffness of the robot manipulator plays a crucial role in improving welding accuracy. Due to the relatively low stiffness, the robot can hardly achieve the specified accuracy under the loading condition. Hence, identifying the joint stiffness and compensating the displacement in Cartesian space is an intuitive work to do in welding industry. Although substantial works had been done on stiffness modeling and identification, the uncertainties existed in transmission and manufacturing were neglected which may affect the manipulator’s stiffness and accuracy to a certain extent, in practice. In this paper, we propose an uncertain approach to identify the stiffness of a welding manipulator KUKA-KR16. Firstly, the uncertainties of the D-H parameters are considered and simulated by Monte-Carlo method. Then, the Cartesian stiffness is identified through an experiment which is composed of API laser tracker and a cable pulley system with deadweights. Finally, combining the previous enhanced stiffness model, we obtain the distribution of the joint stiffness, based on which the compensation results are proved to be effective in Cartesian space.