Robot compliance control framework for grinding thin-walled parts with unknown surface: Deformation and orientation adaptation

Abstract

In the context of intelligent manufacturing, robotic grinding emerges as a pivotal technique that holds profound significance in optimizing production processes, enhancing product quality, and driving the transformation towards a more intelligent manufacturing paradigm. Robotic grinding tasks face significant challenges due to dynamic deformed position, variable stiffness, and uncertain contours resulting from thin-walled parts uncertainties. In this paper, an online force-orientation-motion double-loop controller is proposed. In addition, for comparison purposes, the constant impedance control is also analyzed. The main advantage of the proposed method is that the grinding force is robust to the dynamic disturbances and environmental uncertainties. Compared with traditional control methods that rely on precise environmental modeling, the proposed method enhances adaptability in complex machining environments through robust control based on online system feedback. The experimental results verify the effectiveness of the proposed method in enhancing the grinding quality, improving the force control performance, and handling boundary constraints, demonstrating its suitability for applications involving thin-walled parts with unknown surface.