Ambient Assisted Living and Social Robots: Towards Learning Relations between User’s Daily Routines and Mood

Abstract

Endowing social robots with the ability to learn and predict the user’s activities during the day is one of the main aims of research in the field of ambient assisted living. Social robots should support older adults with daily activity and, at the same time, they should contribute to emotional wellness by considering affective factors in everyday situations. The main goal of this research is to investigate whether it is possible to learn relations between the user’s affective state and daily routines, made by activities, with the aid of a social robot, Pepper in this case. To this aim, we use the WoMan system able to incrementally learn daily routines and the context in which activities take place. WoMan will be used as a back-end module of the Daily Diary application running on the Pepper robot to collect data concerning daily activities and their relation to emotions and mood. Results of this phase of the research will be used to assess the validity of the approach in ambient assisted living houses for seniors to make the social robot able to provide not only proactive service assistance but also an affective empathic experience.