  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.
