A Proactive Robot Tutor Based on Emotional Intelligence
In recent years, social robots are playing a vital role in various aspects of acting as a companion, assisting in regular tasks, health, interaction, teaching, etc. Coming to the case of robot tutor, the actions of the robot are limited. It may not fully understand the emotions of the student. It may continue to give lecture even though the user is bored or left away from the robot. This situation makes a user feel that robot cannot supersede a human being because it is not in a position to understand emotions. To overcome this issue, in this paper, we present an Emotional Classification System (ECS) where the robot adapts to the mood of the user and behaves accordingly by becoming proactive. It works based on the emotion tracked by the robot using its emotional intelligence. A robot as a sign language tutor scenario is considered to assist speech and hearing impairment people for validating our model. Real-time implementations and analysis are further discussed by considering Pepper robot as a platform.
KeywordsSocial robots Emotions ECS Sign language AUSLAN
This research is supported by an Australian Government Research Training Program Scholarship. We are thankful to the University of Technology Sydney and ARC Discovery Project scheme.
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