ENHANCING HUMAN-ROBOT INTERACTION THROUGH GROUP EMOTION RECOGNITION

Abstract

Abstract - This article explores within the field of Human-Robot Interaction (HRI), focusing on the complicated relationship between emotions, decision-making, and robot behaviors. Emotions are essential to effective communication and interaction, requiring the development of emotion recognition systems in robots. The article explores both individual and group emotion recognition, including microexpressions and macroexpressions. Group emotion dynamics, encompassing phenomena like emotional contagion, convergence, and social influence, are separated to understand how emotions combine within collective settings. A concept, Group Emotion Recognition (GER), is introduced, providing a framework for recognizing emotions within groups. GER involves proximity metrics, emotion classification, and entropy-based analysis to quantify emotion diversity. The article also outlines how GER can enhance user engagement, personalize interactions, improve group dynamics, and foster social acceptance in various human-robot interaction scenarios. Decision-making based on GER, driven by positive or negative emotion labels, is discussed, highlighting the adaptability and sensitivity required for effective human-robot interactions. Ethical considerations regarding the use of emotion recognition technology are addressed throughout the article, emphasizing responsible implementation. Overall, this work lays a solid foundation for advancing the field of HRI by integrating emotion recognition and decision-making to create emotionally intelligent and socially aware robots.

Keywords

• human-robot interaction (hri)
• group emotion recognition (ger)
• individual emotion recognition (ier)
• decision making (dm)