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<p>In human-robot interaction, the development of robots’ social capabilities highlights the significant potential of using robots for emotion regulation to enhance interaction. Robot-mediated emotion regulation must be conducted in an appropriate manner, considering the specific context. This study explored how different regulation types impact users’ emotions, decision-making, and interaction experience across various emotional scenarios using a human-subject experiment. The study used a 3 (robot-mediated regulation type: empathetic emotion regulation, non-empathetic emotion regulation, and no regulation) <InlineEquation ID="IEq1"> <EquationSource Format="TEX">\(\times\)</EquationSource> </InlineEquation> 2 (scenario valence: positive or negative) mixed design. Our results showed that both empathetic and non-empathetic emotion regulation effectively regulated participants’ emotions in both positive and negative scenarios. However, the effects of robot-mediated emotion regulation varied across different emotional scenarios. For instance, in positive scenarios, participants who received empathetic regulation were more likely to accept the robot’s suggestions, while in negative scenarios, non-empathetic regulation appeared more effective. In negative scenarios, the robot’s ability was the primary consideration in determining whether to trust it, whereas in positive scenarios, its benevolence and integrity were equally important. The results of this study will help guide the design and implementation of robot-mediated emotion regulation modules in robots.</p>

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Robots with Heart: How Emotion Regulation Shapes Human-Robot Interaction

  • 期刊论文

  • 发表日期：

    2026年1月27日

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  • Lesong Jia,
  • Jackie Ayoub,
  • Danyang Tian,
  • Miao Song,
  • Ehsan Moradi Pari,
  • Na Du

摘要

In human-robot interaction, the development of robots’ social capabilities highlights the significant potential of using robots for emotion regulation to enhance interaction. Robot-mediated emotion regulation must be conducted in an appropriate manner, considering the specific context. This study explored how different regulation types impact users’ emotions, decision-making, and interaction experience across various emotional scenarios using a human-subject experiment. The study used a 3 (robot-mediated regulation type: empathetic emotion regulation, non-empathetic emotion regulation, and no regulation) \(\times\) 2 (scenario valence: positive or negative) mixed design. Our results showed that both empathetic and non-empathetic emotion regulation effectively regulated participants’ emotions in both positive and negative scenarios. However, the effects of robot-mediated emotion regulation varied across different emotional scenarios. For instance, in positive scenarios, participants who received empathetic regulation were more likely to accept the robot’s suggestions, while in negative scenarios, non-empathetic regulation appeared more effective. In negative scenarios, the robot’s ability was the primary consideration in determining whether to trust it, whereas in positive scenarios, its benevolence and integrity were equally important. The results of this study will help guide the design and implementation of robot-mediated emotion regulation modules in robots.