Towards a computational method of scaling a robot's behavior via proxemics

Abstract

Humans regulate their social behavior based on proximity to other social actors. Likewise, when a robot fulfills the role of a social actor it too should regulate its interaction based on proximity. This paper describes work in progress to establish methods for autonomous modification of social behavior based on proximity and to quantify human preferences between methods of scaling a robot's social behaviors based on distance from a human. The preliminary results of a 72 participant human study examine the reaction to scaling with linear methods and perception-based methods. Results indicate significantly higher ratings in multiple areas (comfort, natural movement, safety, self-control, intelligence, likability, submissiveness (p<.05) when using a perception-based scaling function, as opposed to a linear or no scaling function. Work in progress is analyzing the biometric measures collected.