Study of Emotion Recognition Models for Socially Aware Robots and Subsequent Path Mapping

Globally various robots working in harmony to perform a variety of tasks it is extremely important to map a path for hassle-free performance without restrictions and smooth movement even in the most complex situations. A common example of such complex situations is a robot moving in a crowded place full of human beings. The bot must find its way amidst these circumstances without disturbing the overall environmental setup. One such unique method for this to happen is human-robot interaction based on emotions. In this paper, various methods are discussed and present a substantial comparison between different methods of socially aware robotics based on facial expressions and emotions. The methods incorporated are GAIT based emotion learning, Affective Cognitive Learning, and Decision-Making model, and Pleasure-Arousal-Dominance Model.