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?"

Motor resonance mechanisms are known to affect humans' ability to interact with others, yielding the kind of “mutual understanding” that is the basis of social interaction. However, it remains unclear how the partner's action features combine or compete to promote or prevent motor resonance during interaction. To clarify this point, the present study tested whether and how the nature of the visual stimulus and the properties of the observed actions influence observer's motor response, being motor contagion one of the behavioral manifestations of motor resonance. Participants observed a humanoid robot and a human agent move their hands into a pre-specified final position or put an object into a container at various velocities. Their movements, both in the object- and non-object- directed conditions, were characterized by either a smooth/curvilinear or a jerky/segmented trajectory. These trajectories were covered with biological or non-biological kinematics (the latter only by the humanoid robot). After action observation, participants were requested to either reach the indicated final position or to transport a similar object into another container. Results showed that motor contagion appeared for both the interactive partner except when the humanoid robot violated the biological laws of motion. These findings suggest that the observer may transiently match his/her own motor repertoire to that of the observed agent. This matching might mediate the activation of motor resonance, and modulate the spontaneity and the pleasantness of the interaction, whatever the nature of the communication partner.

This study investigated how Parkinson's disease alters haptic perception and the underlying mechanisms of somatosensory and sensorimotor integration. Changes in haptic sensitivity and acuity (the abilities to detect and to discriminate between haptic stimuli) due to Parkinson's disease were systematically quantified and contrasted to the performance of healthy older and young adults. Using a robotic force environment, virtual contours of various curvatures were presented. Participants explored these contours with their hands and indicated verbally whether they could detect or discriminate between two contours. To understand what aspects of sensory or sensorimotor integration are altered by ageing and disease, we manipulated the sensorimotor aspect of the task: the robot either guided the hand along the contour or the participant actively moved the hand. Active exploration relies on multimodal sensory and sensorimotor integration, while passive guidance only requires sensory integration of proprioceptive and tactile information. The main findings of the study are as follows: first, a decline in haptic precision can already be observed in adults before the age of 70 years. Parkinson's disease may lead to an additional decrease in haptic sensitivity well beyond the levels typically seen in middle-aged and older adults. Second, the haptic deficit in Parkinson's disease is general in nature. It becomes manifest as a decrease in sensitivity and acuity (i.e. a smaller perceivable range and a diminished ability to discriminate between two perceivable haptic stimuli). Third, thresholds during both active and passive exploration are elevated, but not significantly different from each other. That is, active exploration did not enhance the haptic deficit when compared to passive hand motion. This implies that Parkinson's disease affects early stages of somatosensory integration that ultimately have an impact on processes of sensorimotor integration. Our results suggest that the known motor problems in Parkinson's disease that are generally characterized as a failure of sensorimotor integration may, in fact, have a sensory origin.

Robots are at the position to become our everyday companions in the near future. Still, many hurdles need to be cleared to achieve this goal. One of them is the fact that robots are still not able to perceive some important communication cues naturally used by humans, e.g. gaze. In the recent past, eye gaze in robot perception was substituted by its proxy, head orientation. Such an approach is still adopted in many applications today. In this paper we introduce performance improvements to an eye tracking system we previously developed and use it to explore if this approximation is appropriate. More precisely, we compare the impact of the use of eye- or head-based gaze estimation in a human robot interaction experiment with the iCub robot and naïve subjects. We find that the possibility to exploit the richer information carried by eye gaze has a significant impact on the interaction. As a result, our eye tracking system allows for a more efficient human-robot collaboration than a comparable head tracking approach, according to both quantitative measures and subjective evaluation by the human participants.

Robots are becoming widespread in society and issues such as information security and overtrust in them are gaining increasing relevance. This research aims at giving an insight into how trust towards robots could be exploited for the purpose of social engineering. Drawing on Mitnick's model, a well-known social engineering framework, an interactive scenario with the humanoid robot iCub was designed to emulate a social engineering attack. At first iCub attempted to collect the kind of personal information usually gathered by social engineers by asking a series of private questions. Then, the robot tried to develop trust and rapport with participants by offering reliable clues during a treasure hunt game. At the end of the treasure hunt, the robot tried to exploit the gained trust in order to make participants gamble the money they won. The results show that people tend to build rapport with and trust toward the robot, resulting in the disclosure of sensitive information, conformation to its suggestions and gambling.

In the last decades, the introduction of robotic devices in fields such as industries, dangerous environments, and medicine has notably improved working practices. The availability of a new generation of humanoid robots for everyday’s activities in human populated environments can entail an even wider revolution. Indeed, not only domestic activities but also social behaviors will adapt to a continuous interaction with a completely new kind of social agents. In the light of this scenario, it becomes crucial to design robots suited to natural cooperation with humans, and contextually to develop quantitative methods to measure human-robot interaction (HRI). Motor resonance, i.e. the activation of the observer’s motor control system during action perception, has been suggested to be a key component of human social behavior, and as such is thought to play a central role for HRI. In the literature there are reports of robots that have been used as tools to understand the human brain. The aim of this review is to offer a different perspective in suggesting that human responses can become a tool to measure and improve robot interactional attitudes. In the first part of the paper the notion of motor resonance and its neurophysiological correlates are introduced. Subsequently we describe motor resonance studies on the perception of robotic agents’ behavior. Finally we introduce proactive gaze and automatic imitation, two techniques adopted in human motor resonance studies, and we present the advantages which would follow their application to HRI.