Emotion Recognition in Human–Robot Interaction Using the NAO Robot

Abstract

Affective computing can be implemented across many fields in order to provide a unique experience by tailoring services and products according to each person’s needs and interests. More specifically, digital learning and robotics in education can benefit from affective computing with a redesign of the curriculum’s contents based on students’ emotions during teaching. This key feature is observed during traditional learning methods, and robot tutors are adapting to it gradually. Following this trend, this work focused on creating a game that aims to raise environmental awareness by using the social robot NAO as a conversation agent. This quiz-like game supports emotion recognition with DeepFace, allowing users to review their answers if a negative emotion is detected. A version of this game was tested during real-life circumstances and produced favorable results, both for emotion analysis and overall user enjoyment.