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.
@cite_8: In conjunction with what is often called the industry 4.0, the new machine age, or the rise of the robots, the authors of this paper have each experienced the following phenomenon. At public events and roundtable discussions, among our circles of friends, or during interviews with the media, we are asked on a surprisingly regular basis: "How must humankind adapt to the imminent process of technological change? What do we have to learn in order to keep pace with the smart new machines? What new skills do we need to understand the robots?"
The field of HRI has been the focus of many research efforts during the last few decades. A key observation is that, successful human-robot collaborations requires that the human has to understand the robot and, simultaneously, that the robot is also able to understand the human actions @cite_8 . This has propelled fields such as robotics, computer vision, human cognition, psychology, and neuroscience, to combine resources in the aim of proposing techniques that tackle those intertwined issues.