Contour error-based optimization of the end-effector pose of a 6 degree-of-freedom serial robot in milling operation

Abstract

• A pose optimization method is proposed to improve the contour accuracy of robotic milling by minimizing contour errors induced by the low posture-dependent stiffness. • The deformation errors induced by cutting forces are predicted based on the robot stiffness model and simulated cutting forces. • A comprehensive contour error index is defined by integrating the statistical properties of contour errors. • Under the constraints of kinematics and smoothness, the optimal tool poses are obtained by minimizing contour error index through a discrete searching algorithm . • Simulation and experimental results show that the contour accuracy can be significantly improved using the proposed strategy when compared with traditional methods. Robot manipulators with 6 degree-of-freedom (DOF) have advantages of good flexibility and large working space. However, the relatively low stiffness deteriorates the machining accuracy and stability in robotic milling tasks, which restricts the widely application of robotic milling in industry. To increase the machining accuracy, taking advantage of a redundant degree of freedom of the robot, this paper presents a method to optimize the pose of the milling robot by taking the contour error as the optimization index. Firstly, the cutting forces are predicted in advance for a given milling task, and the deformations of the robot end-effector (EE) are calculated based on the stiffness model and cutting forces at all cutting locations (CLs). Secondly, the contour errors of the machined product are calculated based on the deformation errors and the tool path profile. Finally, the optimal tool poses are obtained by minimizing contour error through a discrete searching algorithm under the kinematic and smoothness constraints. Compared with optimization indexes used in existing studies, the main contributions of the proposed index lie on two aspects. First, the cutting force variances at different CLs are considered. Second, the contour accuracy is taken as a direct optimization index. Therefore, the proposed method is able to improve the form accuracy of robotic milling better than existing studies which use stiffness as the evaluation index. Simulation and experiments show that the robot trajectory optimized by the proposed method can significantly improve the machining accuracy compared with un-optimized results and existing studies.