Modelling social interaction between humans and service robots in large public spaces

With the advent of service robots in public places (e.g., in airports and shopping malls), understanding socio-psychological interactions between humans and robots is of paramount importance. On the one hand, traditional robotic navigation systems consider humans and robots as moving obstacles and focus on the problem of real-time collision avoidance in Human-Robot Interaction (HRI) using mathematical models. On the other hand, the behavior of a robot has been determined with respect to a human. Parameters for human-human interaction have been assumed and applied to interactions involving robots. One major limitation is the lack of sufficient data for calibration and validation procedures. This paper models, calibrates and validates the socio-psychological interaction of the human in HRIs among crowds. The mathematical model is an extension of the Social Force Model for crowd modelling. The proposed model is calibrated and validated using open source datasets (including uninstructed human trajectories) from the Asia and Pacific Trade Center shopping mall in Osaka (Japan).In summary, the results of the calibration and validation on the multiple HRIs encountered in the datasets show that humans react to a service robot to a higher extend within a larger distance compared to the interaction range towards another human. This microscopic model, calibration and validation framework can be used to simulate HRI between service robots and humans, predict humans' behavior, conduct comparative studies, and gain insights into safe and comfortable human-robot relationships from the human's perspective.