Contact-Based in-Hand Package Pose Estimation Using a Collaborative Robot

In automated robot assembly and industrial palletization tasks it is crucial to ensure a good accuracy while placing objects given a planned target pose. To achieve this goal post-grasp strategies may be adopted that estimate or correct the displacement error between the expected and the actual grasp pose of an object. Standard in-hand post-grasp strategies require sensors like cameras to estimate the displacement error while the object is grasped. Other approaches are based on object re-grasping using special jigs and fixtures. In this paper a novel post-grasp strategy is proposed, where the displacement error is estimated in-hand by detecting collisions between the grasped object and a fixed peg. The proposed method estimates the displacement error after few collisions. The approach was evaluated on cardboard boxes thanks to the internal forcetorque sensor of a collaborative robot, achieving sub-millimeter and sub-degree residual placement errors.