Robot stiffness modeling based on the rigid flexible coupling simulation and its application to trajectory planning

The flexibility of joints has the major influence on the robot stiffness, which makes it limited in the field of precision and ultra-precision machining. How to ensure the end-effector stiffness of the robot has been one significant problem for the above application. To address this challenge, in this work, a rigid-flexible coupling simulation method is proposed for the robot, then based on the simulation, the robotic end-effector stiffness prediction model is established, which can be applied to the robotic trajectory planning to control its end-effector stiffness. In the simulation method, the rigid-flexible simulation model of the robot is established based on the torsional stiffness estimation of each joint and its global decomposition in multiple directions of robotic base coordinate system. During the stiffness modeling, the neural network theory is used to establish a mapping model between robotic pose and end-effector stiffness based on the sample data accumulated by simulations under different poses. In order to show the significance of this work, an application case to the trajectory planning problem is performed. The results analysis, indicates that the proposed algorithm can control the end-effector stiffness not less than the required value during the whole robotic operation.