Robotic cutting is a challenging contact-rich manipulation task where the robot must simultaneously negotiate unknown object mechanics, large contact forces, and precise motion requirements. We introduce a new active virtual-model control scheme that enables knife rocking motion for robot manipulators, without pre-planned trajectories or precise information of the environment. Motion is generated and controlled through switching virtual coupling with virtual mechanisms, given by virtual springs, dampers, and masses arranged in a suitable way. Through analysis and experiments, we demonstrate that the controlled robot behavior settles into a periodic motion. Experiments with a Franka manipulator demonstrate robust cuts with five different vegetables, and sub-millimeter slice accuracy from 1 mm to 6 mm at nearly one cut per second. The same controller survives changes in knife shape and cutting board height, and adaptation to a different humanoid manipulator, demonstrating robustness and platform independence.

翻译：机器人切割是一项具有挑战性的密集接触操作任务，机器人必须同时应对未知的物体力学特性、巨大的接触力以及精确的运动要求。我们提出了一种新的主动虚拟模型控制方案，该方案能使机器人机械臂实现刀具的摇摆运动，而无需预先规划轨迹或环境的精确信息。运动是通过与虚拟机构进行切换式虚拟耦合来生成和控制的，这些虚拟机构由以适当方式排列的虚拟弹簧、阻尼器和质量块构成。通过分析和实验，我们证明受控的机器人行为会收敛为一种周期性运动。使用Franka机械臂进行的实验表明，该方法能对五种不同的蔬菜实现鲁棒的切割，并在接近每秒一次的切割频率下，实现从1毫米到6毫米的亚毫米级切片精度。同一控制器在刀具形状和砧板高度发生变化时依然有效，并能适应不同的人形机械臂，这证明了其鲁棒性和平台无关性。