Exploring Cognitive Models in Human-Robot Interaction

Abstract

This paper explores the role of cognitive models in Human-Robot Interaction (HRI), emphasising their importance in enhancing robots' adaptability, emotional intelligence, and collaboration with humans. It examines key advancements in adaptive learning, affective computing, and context-aware decision-making while addressing ethical considerations like privacy, bias, and autonomy. Despite progress, challenges remain in improving context awareness and emotional recognition. The paper calls for further interdisciplinary research, the development of comprehensive ethical frameworks, and the use of Explainable AI (XAI) to foster trust. Future directions include expanding HRI applications in education, healthcare, and social care, aiming for robots that are effective, empathetic, and aligned with human values.