Robotic sensory perception on human mentation for offering proper services

Abstract

To interact with humans in Human Social Environments (HSEs), robots are expected to possess the ability of situational context perception and behave appropriately. In this paper, we propose two deep learning models, as situational context perception of robot, to learn from observations of human-robot interaction. Based on these models, we endow robot the capability of perceiving human's mentation. Thus, the appropriate social behaviors can be performed by the robot with respect to human's mental state. The experimental results demonstrate that robot can significantly improve the accuracy of predicting a person's mentation through the proposed deep learning models by comparison to conventional classifiers and possess potential of providing agreeable serving.