Situation Awareness for Proactive Robots in HRI

Perception of the intention of humans prior to an interaction is a demanding skill during human-robot interaction (HRI). This skill is even more sought after during robot-initiated HRI. Initiating an interaction in an inappropriate situation can be avoided when robots are equipped with the ability to decide when to interact and when not to. Many of the existing systems investigate only a few characteristics of humans which demonstrate inner state of mind and are based on complex monitoring mechanisms which limit their use in most of the scenarios. This work presents an autoregressive model based on observable physical and emotional human cues to determine the level of interest displayed by a human towards an interaction with a robot. This model was implemented on a service robotic platform and the behavior of the robot was controlled using the model. The behavior of the robot was determined by means of proxemic approach and the nature of conversation with the human. The outcomes of the model were evaluated by analyzing user feedback in different situations inside a simulated social environment. Using the model, robot was given the ability to analyze the situation of its human user in an emotionally intelligent manner, prior to an interaction. The behavior of the model was reviewed by user feedback in order to validate the findings. Results of the experiment are presented and findings of the study are discussed.