Modelling and Control of Object Handover, A Study in Human-Robot Interaction

Object handover is a common physical interaction between humans. It is thus also of signi cant interest for human-robot interaction. In this work, we are focused on robot-tohuman object handover. To implement the task on the robot, the con guration (position and orientation) in which the object is transferred should be selected so that the handover is safe and comfortable for the human. The trajectory along which the robot moves the object to the point of transfer should be also selected so that the robot intention is clear and the handover feels natural to the human. We propose to select the con guration for the transfer and the trajectory to reach this con guration based on what humans do in human-human handover. We describe a human study designed to investigate the human-human handover and propose an ergonomic model that can predict object transfer position observed in the study. A humanrobot experiment is then conducted that shows that the proposed model generates transfer positions that match the preferred height and distance relative to the human. Another signi cant challenge in robot-to-human handover is how to reduce the failure rate, i.e., ensuring that the object does not fall (object safety), while at the same time allowing the human to easily acquire the object (smoothness). To endow the robot with a failure recovery mechanism, we investigate how humans detect failure during the transfer phase of the handover. We conduct a human study that shows that a human giver primarily relies on vision rather than haptic sensing to detect the fall of the object. Motivated by this study, a robotic handover system is proposed that consists of a motion sensor attached to the robot's gripper, a force sensor at the base of the gripper, and a controller that is capable of re-grasping the object if it starts falling. The proposed system is implemented on a Baxter robot and is shown to achieve a smooth and safe handover.