Fast Handovers with a Robot Character: Small Sensorimotor Delays Improve Perceived Qualities We present a system for fast and robust handovers with a robot character, together with a user study investigating the effect of robot speed and reaction time on perceived interaction quality. The system can match and exceed human speeds and confirms that users prefer humanlevel timing.The system has the appearance of a robot character, with a bearlike head and a soft anthropomorphic hand and uses Bezier curves to achieve smooth minimumjerk motions. Fast timing is enabled by low latency motion capture and realtime trajectory generation: the robot initially moves towards an expected handover location and the trajectory is updated onthefly to converge smoothly to the actual handover location. A hybrid automaton provides robustness to failure and unexpected human actions.In a 3x3 user study, we vary the speed of the robot and add variable sensorimotor delays. We evaluate the social perception of the robot using the Robot Social Attribute Scale (RoSAS). Inclusion of a small delay, mimicking the delay of the human sensorimotor system, leads to an improvement in perceived qualities over both no delay and long delay conditions. Specifically, with no delay the robot is perceived as more discomforting, and with a long delay it is perceived as less warm.

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.