  Human interaction involves very sophisticated non-verbal communication skills
like understanding the goals and actions of others and coordinating our own
actions accordingly. Neuroscience refers to this mechanism as motor resonance,
in the sense that the perception of another person's actions and sensory
experiences activates the observer's brain as if (s)he would be performing the
same actions and having the same experiences. We analyze and model non-verbal
cues (arm movements) exchanged between two humans that interact and execute
handover actions. The contributions of this paper are the following: (i)
computational models, using recorded motion data, describing the motor
behaviour of each actor in action-in-interaction situations, (ii) a
computational model that captures the behaviour if the "giver" and "receiver"
during an object handover action, by coupling the arm motion of both actors,
and (iii) embedded these models in the iCub robot for both action execution and
recognition. Our results show that: (i) the robot can interpret the human arm
motion and recognize handover actions; and (ii) behave in a "human-like" manner
to receive the object of the recognized handover action.
