To be seamlessly integrated in human-centered environments, robots are expected to have intelligent social capabilities on top of their physical abilities. To this end, research in artifi-cial intelligence and human-robot interaction face two major challenges. Firstly, robots need to cope with uncertainty during interaction, especially when dealing with factors that are not fully observable and hard to infer (latent variables) such as the states representing the dynamic environment and human behavior (e.g., intents, goals, preferences). Secondly, robots need to communicate their behaviors to agents (humans and other robots in the environment) in a clear and understandable manner. Therefore, robots need to be context-aware: being able to perceive and understand their surroundings, and adapt their functionalities accordingly.

Imitation is of major importance during social interactions, would it be between humans or between a human and a robot. This is even more true when considering users with special needs. In this paper, we describe an experimental imitation task protocol using a robot Nao that we designed to assess whether sensory profiles of children with Autistic Spectrum Disorder (ASD) influence their capabilities to imitate or to initiate gestures that are going to be imitated. We based our work on the hypothesis that children with an overreliance on proprioceptive cues and hyporeactivity to visual cues have a greater difficulty imitating and improve their skills more slowly than children with an overreliance on visual cues and hyporeactivity to proprioceptive cues. Twelve children and teenagers with ASD participated in seven imitation sessions over eight weeks. As expected, we observed that children with an overreliance on proprioceptive cues and hyporeactivity to visual cues had more difficulties imitating the robot than the other children. Moreover, the repeated sessions revealed to have positive effects on social behaviors displayed by all children (gaze to the partner, imitations) toward a human partner after the sessions with the robot. We conclude on the possible impacts of such results on the design of social human-robot interactions for users with ASD.

Individuals suffering from Autistic Spectrum Disorder (ASD) have impaired skills in social communication and joint attention. In this paper, we explain how we designed and evaluated a Joint Attention (JA) task for individuals with ASD using the Nao humanoid robot. The interaction was tested in children and teenagers with ASD (N=11). Their proprioceptive and visual integration of cues were first assessed, with the hypothesis that individuals with an overreliance on proprioceptive cues and with a hyporeactivity to visual cues would have more difficulties conducting successful interactions with the robot. We observed that participants with an overreliance on proprioceptive cues and hyporeactivity to visual cues showed different behaviors in responding to joint attention. They followed the prompting of the Nao robot more slowly than individuals with an overreliance on visual cues and a hyporeactivity to proprioceptive cues. Defining such individual profiles prior to the social interaction with a robot and working closely with caregivers could provide promising strategies for designing successful and adapted Human-Robot Interaction (HRI) for individuals with ASD.

In this paper, we describe the elaboration and the validation of a body and face database1, of 96 videos of 1 to 2 seconds of duration, expressing 4 emotions (i.e., anger, happiness, fear, and sadness) elicited through 4 platforms of increased visual complexity and level of embodiment. The final aim of this database is to develop an individualized training program designed for individuals suffering of autism in order to help them recognize various emotions on different test platforms: two robots, a virtual agent, and a human. Before assessing the recognition capabilities of individuals with ASD, we validated our video database on typically developed individuals (TD). Moreover, we also looked at the relationship between the recognition rate and their personality traits (extroverted (EX) vs. introverted (IN)). We found that the personality of our TD participants did not lead to a different recognition behavior. However, introverted individuals better recognized emotions from less visually complex characters than extroverted individuals.