A Systematic Review of Emotion Recognition and Non-Verbal Communication in Human-Robot Interaction

This study aims to systematically examine prior research on non-verbal communication patterns within human-robot interaction (HRI), including methodological approaches, study characteristics, and context-specific findings. As robotics continues to evolve, there is a growing emphasis on equipping robots with capabilities for social and emotional engagement. Despite their widespread application, many mobile robots - especially non-anthropomorphic ones - are limited in their ability to convey affective signals due to their lack of facial expressiveness. This constraint poses significant challenges for creating intuitive and natural interactions between humans and robots. To address this issue, the present review follows PRISMA guidelines in conducting a structured analysis of the literature. The systematic search, conducted via the EBSCO Discovery Service, initially yielded 114 publications. After a rigorous selection process, six studies were deemed relevant and included in the final synthesis. These studies reveal that robots’ physical gestures can be as interpretable as those of humans, underscoring the critical role of non-verbal cues in HRI. Moreover, the ability of users to accurately perceive robotic emotions appears to be influenced by individual personality traits, with notable effects related to confidence and emotional valence. The results point to the necessity of designing robotic systems that not only communicate emotions effectively but also reinforce user trust in their interpretations. In light of Industry 5.0’s emphasis on human-centric automation, enhancing non-verbal expressivity in robots could be pivotal. Moving forward, research should prioritize underexplored aspects of emotional perception and user diversity to foster more adaptive and socially responsive robotic systems.