Optimization of robot posture and spindle speed in robotic milling

In robotic machining, most of the existing research has been done to improve the machining performance by optimizing the robot posture. However, spindle speed also plays an important role in improving machining performance. In this paper, a robot posture and spindle speed optimization method is proposed to improve the machining performance in robotic milling. First, the frequency response function is measured by the modal test. Based on the measured frequency response function, the frequency response function of the remaining redundant angle and machining position is predicted by the Gaussian process regression model. Next, the profile error is obtained based on the predicted frequency response function and the simulated milling force. The machining performance index in robotic milling is given on the basis of the profile error. Then, the Intelligible-in-time Logics algorithm (ILA) is introduced to find the optimal robot posture and spindle speed based on the machining performance index. In addition, the machining performance index threshold is specified to reduce the redundant angle and spindle speed variation for practical requirements. Finally, the optimized robot posture and spindle speed can further improve the machining performance in robotic milling, which is verified by the robotic milling experiment. The experimental results show that the proposed method can reduce the peak acceleration by 46.82% for the same machining path.