Force-sensing-based compliant error compensation control for robotic milling of weak-stiffness thin-walled components

Industrial robots hold considerable potential in the field of milling operations. However, due to their structural characteristics, significant machining errors often occur during the milling process. For the robotic milling, existing research rarely provides direct control strategies for machining error compensation, which limits the further application of industrial robots in high-precision machining tasks. To enhance the robotic milling accuracy, this paper proposes an error compensation control method based on force sensing. First, to predict the relationship between cutting forces and machining parameters, an improved cutting force model is developed by introducing the material removal parameter S_l. Combining the cutting force signals with the robot's position data, the machining error can be predicted. Furthermore, by considering the stiffness characteristics of both the robot and the workpiece, an error compensation control method is proposed. The initial milling trajectory is generated using the robot’s spatial pose and the workpiece model. Based on force sensing and the desired machining accuracy, the cutting parameters are adaptively adjusted. A data-driven adaptive parameter adjustment strategy is further proposed by integrating robot motion data, machining data, and cutting force signals. By adjusting the feed rate in different out-of-tolerance regions, a new compensated milling trajectory is generated to correct machining errors. To validate the effectiveness of the proposed method, robotic milling experiments were conducted on thin-walled light alloy workpieces and feature components. The experimental results demonstrate that the proposed approach significantly reduces machining errors in robotic milling, thereby improving both machining quality and efficiency. These results indicate that the proposed method has strong potential for high-precision robotic milling of complex thin-walled structures.