We propose a robotic manipulation system that can pivot objects on a surface using vision, wrist force and tactile sensing. We aim to control the rotation of an object around the grip point of a parallel gripper by allowing rotational slip, while maintaining a desired wrist force profile. Our approach runs an end-effector position controller and a gripper width controller concurrently in a closed loop. The position controller maintains a desired force using vision and wrist force. The gripper controller uses tactile sensing to keep the grip firm enough to prevent translational slip, but loose enough to induce rotational slip. Our sensor-based control approach relies on matching a desired force profile derived from object dimensions and weight and vision-based monitoring of the object pose. The gripper controller uses tactile sensors to detect and prevent translational slip by tightening the grip when needed. Experimental results where the robot was tasked with rotating cuboid objects 90 degrees show that the multi-modal pivoting approach was able to rotate the objects without causing lift or slip, and was more energy-efficient compared to using a single sensor modality and to pick-and-place. While our work demonstrated the benefit of multi-modal sensing for the pivoting task, further work is needed to generalize our approach to any given object.

翻译：我们提出了一种机器人操作系统，该系统能够利用视觉、腕部力觉和触觉传感在平面上旋转物体。我们旨在通过允许旋转滑动，同时维持期望的腕部力轮廓，来控制物体绕平行夹爪夹持点的转动。我们的方法闭环并行运行末端执行器位置控制器和夹爪宽度控制器。位置控制器利用视觉和腕部力维持期望的力。夹爪控制器利用触觉传感保持足够的夹持力以防止平移滑动，但保持松弛以诱发旋转滑动。这种基于传感器的方法依赖于匹配从物体尺寸和重量导出的期望力轮廓，以及基于视觉的物体姿态监测。夹爪控制器利用触觉传感器检测并防止平移滑动，必要时收紧夹持。实验任务要求机器人将立方体物体旋转90度，结果表明多模态旋转方法能够在不引起抬升或滑动的情况下旋转物体，并且相比于使用单一传感器模态以及拾取-放置操作，该方法具有更高的能效。虽然我们的工作证明了多模态传感在旋转任务中的优势，但进一步的工作需要将该方法推广到任意给定的物体。