Coupling of Arm Movements during HumanRobot Interaction: the handover case Collaboration involves understanding the action of others, as well as acting in a way that can be understood by others. One of those tasks is the handover. In this paper, we study the behaviour of humans during the handover and design the mechanisms allowing a robot to learn from that behaviour.We analyse and model the arm movements of humans while handing over objects to one another. The contributions of this paper are the following: (i) a computational model that captures the behaviour of the xe2x80x9cgiverxe2x80x9d and xe2x80x9creceiverxe2x80x9d of the object, by coupling the arm motion; (ii) discuss this approach amidst a previous coupling strategy; and (iii) embedded the model in the iCub robot for human to robot handovers.Our results show that: (i) the robot can coordinate with the human to timely and safely receive the object; (ii) the robot behaves in a xe2x80x9chumanlikexe2x80x9d manner while receiving the object; and (iii) our approach has significant advantages to the previous approach.

An Evaluation of RobottoHuman Handover Configurations for Commercial Robots The handover of objects is a fundamental task in robothuman interaction. The nature of the handover can be varied by adjusting various parameters in order to achieve a humanlike interaction. In this paper the final handover configuration is examined and analyzed. For this purpose, we conducted an experiment in which subjects taught a robot proper and improper end poses for different objects in different situations. We analyze the learned poses to determine what factors proper poses depend on. In addition to the poses, the configurations of the individual joints of the commercial robot are evaluated. Our results demonstrate that proper poses can be grouped into three clusters. These differ mainly in the rotation of the forearm. The height of a proper handover is also determined based on external factors.