Graphically Representing Child-Robot Interaction Proxemics

This paper discusses the current analysis of a large set of child-robot interaction experiments, in which a 2-4 year old child plays a set of games with a small humanoid robot, with the goal of detecting early signs of autism in toddlers based on the interactions. Our first goal in this paper is to condense and display these child-robot interactions as multi-channel time series, starting with the distances between the child, robot, parent, and experimenter.  Our second goal is to use these data displays to compare and contrast different children, with the aim of clustering children with similar interaction patterns.  Using a ceiling-mounted camera, we record the interaction between a child and a robot which performs different games and dances.  After analyzing the video footage for the locations of all people and the robot in the room over the variable length of the interaction, we condense the interactions into simplified, quantifiable, scale-invariant data.  We show how the distances between the child and robot, experimenter, and caregiver can be discretized into a few location zones and compared across children using classic similarity measures.  Proxemics (social distances) between the child, robot, caregiver, and experimenter during a child-robot interaction show differences between participants and hence can provide additional information for behavior analysis.