Affect-sensitive human-robot cooperation - theory and experiments

Abstract

A novel affect-sensitive human-robot cooperative framework is presented in this paper. Peripheral physiological indices are measured through wearable biofeedback sensors to detect the affective states of the human. Affect recognition is performed through both quantitative and qualitative analyses. A subsumption control architecture that is sensitive to the affective states of the human is proposed for a mobile robot. Human-robot cooperation experiments are performed where the robot senses the affective state of the human and responds appropriately. The results presented here validate the proposed framework and demonstrates a new way of achieving implicit communication between a human and a robot.