This paper proposes a robot posture optimization method and a workpiece setup optimization approach for robotic milling to improve machining quality.
A force-induced error index is established by considering spindle weight and milling force, along with the identification of spindle gravity and center of mass. A robot posture optimization model is then formulated based on the force-induced error and motion smoothness, and solved using the artificial potential field method. Finally, a bi-level optimization algorithm is applied to address the coupled optimization of robot posture and workpiece setup.
Experimental results show that the proposed robot posture optimization method ensures high computational efficiency and improved machining quality. Moreover, the bi-level workpiece setup optimization further enhances machining accuracy.
The proposed method improves machining quality by simultaneously optimizing tool orientation and redundant degree of freedom, while maintaining high computational efficiency. The bi-level optimization enables simultaneous optimization of workpiece setup and robot posture.
