A Wireless Force-Sensing and Model-Based Approach for Enhancement of Machining Accuracy in Robotic Milling

Abstract

Multiaxis machining (e.g., milling) of large aerospace structures is typically carried out using large monument scale expensive computer numerical control (CNC) machine tools. In contrast, multiple degree-of-freedom-articulated robotic arm-based machining has several potential advantages over CNC machine tools, owing to its flexibility (reconfigurability) and lower cost. However, its application is limited by its much lower stiffness and accuracy compared with a CNC machine tool. This paper presents a new method that combines wireless force sensing with a mechanistic model of the milling process to increase the accuracy of robotic milling while preserving its flexibility. Articulated-arm robotic milling experiments are conducted to validate the concept. Experimental results show significant improvement (> 70%) in the dimensional accuracy of simple geometric features machined using the new method.