Comfortability Analysis Under a Human–Robot Interaction Perspective

Abstract

Interactions entail a tangled mix of emotional states that emerge between the people who are communicating. Being capable of comprehending these states help us to adapt to our partner’s needs enhancing the interaction. In the same fashion, we believe that robots capable of such skills would be better integrated in society. Hence, this paper tackles the internal state that focuses on the unfolding of any social exchange: Comfortability. It explores whether a humanoid robot can have an impact on humans Comfortability and explores the way people might behave. To this aim, the iCub robot interviewed 29 non-HRI researchers for a real column of the IIT Opentalk online magazine. During the interview the robot complimented, ignored, interrupted, and insulted the participant with the intention of making them feel opposite Comfortability levels. The results concluded that a humanoid robot can affect people’s Comfortability highlighting that not everyone perceives, assimilates, and reacts to the same situations in the same way. The findings suggest that self-reports and Valence/Arousal estimations are not reliable measures to determine someone’s Comfortability and that external factors (e.g., attitude towards robots or the robot’s perception) might affect it. On top of that, a list of 28 visual features associated with low Comfortability levels is included, providing support to keep unraveling Comfortability in further studies.