Human-Robot Interaction Using Affective Cues

Abstract

This paper presents a closed loop human-robot interaction framework where a robot can infer the implicit affective cues of the human and respond to them appropriately. Affective cues are inferred by the robot in realtime using psychophysiological analysis where the physiological signals are measured through wearable biofeedback sensors. A robot-based basketball game is designed where a robotic "coach" monitors the participant's anxiety to alter the difficulty level of the game in a real-time closed loop manner according to each participant's performance and anxiety. The results are compared with situations when anxiety is not monitored and the game is adapted only according to the performance. Results show that monitoring and responding to affective cues led to higher performance improvement of the majority of the participants under lower anxiety