A fail-safe object handover controller

Abstract

Humans rely on a multitude of senses to achieve a safe handover. The challenge for a robot-human handover is to both equip the robot with the appropriate sensors as well as devise handover controllers that effectively use them to prevent failures. In this paper we use object acceleration as an indicator of an impending handover failure and propose a handover controller that has re-grasping mechanism to prevent falling of the object in case of an imperfect handover. The work is motivated by our observation that humans primarily rely on vision to prevent handover failure. We also propose a novel acceleration sensing setup that can be integrated into a robot gripper. The handover controller is implemented on Baxter Research robot equipped with the proposed sensor and is shown to be effective in preventing object fall.