Non-facial and non-verbal affective expression for appearance-constrained robots used in victim management

Non-facial and non-verbal methods of affective expression are essential for naturalistic social interaction in robots that are designed to be functional and lack expressive faces (appearance-constrained) such as those used in search and rescue, military, industry, and law enforcement applications. This research identifies five main methods of non-facial and non-verbal affective expression (body movements, postures, orientation, color, and sound) and ranks their effectiveness for appearance-constrained robots operating within the intimate (contact – 0.46 m), personal (0.46 – 1.22 m), and social (1.22 – 3.66 m) proximity zones of a human corresponding to inter-agent distances of approximately three meters or less. This leads to design guidelines for retroactively adding affective expression through software to a robot with little or no physical modifications. To confirm that humans respond more favorably to an affective appearance-constrained robot, a study was conducted with 128 participants and two robots (iRobot Packbot Scout and an Inuktun Extreme-VGTV) in a high fidelity simulated disaster site. Four methods of evaluation were utilized: (1) self-assessments, (2) psychophysiological measures (EKG, abdominal respiration, thoracic respiration, blood volume pulse, skin conductance response), (3) video recording from four different camera perspectives that are currently being coded for behavioral responses, and (4) an audio recorded follow-up interview. This is the largest and most comprehensive controlled study performed in HRI to date. Details of the study design, implications for HRI and robot design, results, video, and current/future research directions will be presented.