Abstract
Companion robots play an important role to accompany humans and provide emotional support, such as reducing human social isolation and loneliness. Based on recognizing human partner's mental states, a companion robot is able to dynamically adjust its behaviors, and make human-robot interaction smoother and natural. Human emotion has been recognized by many modalities like facial expression and voice. Neurophysiological signals have shown promising results in emotion recognition, since it is an innate signal of human brain which cannot be faked. In this paper, emotional state recognition using a neurophysiology method is studied to guide and modulate companion-robot navigation to enhance its social capabilities. Electroencephalogram (EEG), a type of neurophysiological signals, is used to recognize human emotional state, and then feed into a navigation path planning algorithm for controlling a companion robot's routes. Simulation results show that mobile robot presents navigation behaviors modulated by dynamic human emotional states.
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