Industrial robots are typically not used for milling of hard materials due to their low stiffness compared to traditional machine tools. Due to milling being a five degree of freedom (dof) operation, a typical six dof serial manipulator introduces a redundant degree of freedom in the robot pose. This redundancy can be exploited to optimize the pose of the robot during milling to minimize force-induced deflections at the end-effector. Stiffness modeling and optimization techniques for industrial robots utilizing both static (no mass and damping terms) and dynamic (mass and damping terms included) models exist. This paper presents a comparative study of robot pose optimization using static and dynamic stiffness models for different cutting scenarios. Milling experiments show that while a dynamic model-based robot pose optimization yields significant improvement over a static model-based optimization for cutting conditions where the time varying cutting forces approach the robot's natural frequencies, a static model-based optimization is sufficient when the frequency content of the cutting forces are not close to the robot's natural frequencies.

与传统机床相比，由于工业机器人的刚性较低，因此通常不用于铣削硬质材料。由于铣削是五自由度（dof）操作，典型的六自由度串行操纵器在机器人姿态中引入了冗余的自由度。可以利用这种冗余来优化铣削过程中机器人的姿势，以最大程度地减小末端执行器上的力引起的偏转。存在利用静态（无质量和阻尼项）和动态（包括质量和阻尼项）模型的工业机器人的刚度建模和优化技术。本文对使用静态和动态刚度模型的机器人姿势优化进行了比较研究，以用于不同的切割场景。