Optimization of Robot Milling Accuracy Based on a New Stiffness Performance Index

The main factor limiting the widespread use of industrial robots in machining applications is the relatively low stiffness of the robot. Stiffness performance not only affects the quality of robotic milling but also affects the accuracy of the milling process. It is necessary to improve the stiffness performance in the robotic machining process. A new robot stiffness performance index is proposed to evaluate the robot stiffness in the direction normal to the surface of the workpiece to be machined. This index is based on the functional redundancy characteristics of the robot. The relationship between the redundant axis angle and the stiffness performance index at a random point in Cartesian space, and the stiffness performance index values on a random path in Cartesian space are obtained. The robot posture optimization model is established and a new robot milling posture optimization method is introduced. The experimental results prove a significant reduction in machining error and a significant increase in machining accuracy after using the proposed robotic milling posture optimization method, which proves the validity of the proposed stiffness performance index, and the robot milling posture optimization method can be widely used in the industry. Finally, the distribution of stiffness performance index is analyzed to predict the regions of better robot stiffness performance in the workbench, which can be used as a criterion before the milling operation to optimize the robot configuration to improve milling accuracy and save time.