Emotion Regulation in Human-Robot Interaction: Insights from Video and Game Simulations

Abstract

As robots increasingly evolve from functional service providers into social agents, the ability to regulate human emotions during human-robot interaction has become a critical research focus. This study examines how different robot-provided emotion regulation strategies—empathetic, nonempathetic, and no regulation—influence users’ emotional responses, decision-making, and perceptions of trust and interaction quality across both positive and negative emotional contexts. We conducted two complementary studies: a video-based simulation and a game-based simulation. Results demonstrated that empathetic regulation enhanced suggestion acceptance and trust in positive scenarios, while nonempathetic regulation supported more rational decision-making in negative scenarios. Furthermore, video-based simulations elicited stronger emotional arousal and valence shifts, whereas game-based simulations, provided greater ecological validity. Across both methods, participants’ emotional states significantly impacted their evaluations of the robot and the interaction. These findings underscore the importance of adapting emotion regulation strategies to emotional context and offer methodological guidance for simulation-based research in emotionally aware HRI systems.