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<p>Social games offer a rich and challenging environment to develop and evaluate complex robot behaviors. Social interactions with robots benefit from personalization, which requires person identification—a process that raises privacy concerns. Soft biometrics, however, offer a privacy-preserving alternative by enabling short-term identification without relying on private or sensitive features. In this work, we leverage a zero-shot Visual Question Answering (VQA) person identification system and adapt it to make Pepper play <i>Guess Who?</i> The identification module performance is firstly studied offline in the AveRobot dataset. Afterwards, it is integrated in a ROS based architecture that manages the game flow and enables natural verbal interaction. Experiments conducted with 29 subjects demonstrate that the system achieves identification performance nearly equivalent to that of hard biometric-based systems while also offering engaging and entertaining gameplay. Notably, user feedback reveals a high level of acceptance, highlighting that social gaming with robots is a promising avenue for developing and testing complex behaviors.</p>

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Pepper Plays: Guess Who?

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2026年2月23日

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  • Juan Echevarria,
  • Modesto Castrillón-Santana,
  • Igor Rodriguez,
  • Javier Lorenzo-Navarro,
  • Elena Lazkano,
  • Unai Zabala

摘要

Social games offer a rich and challenging environment to develop and evaluate complex robot behaviors. Social interactions with robots benefit from personalization, which requires person identification—a process that raises privacy concerns. Soft biometrics, however, offer a privacy-preserving alternative by enabling short-term identification without relying on private or sensitive features. In this work, we leverage a zero-shot Visual Question Answering (VQA) person identification system and adapt it to make Pepper play Guess Who? The identification module performance is firstly studied offline in the AveRobot dataset. Afterwards, it is integrated in a ROS based architecture that manages the game flow and enables natural verbal interaction. Experiments conducted with 29 subjects demonstrate that the system achieves identification performance nearly equivalent to that of hard biometric-based systems while also offering engaging and entertaining gameplay. Notably, user feedback reveals a high level of acceptance, highlighting that social gaming with robots is a promising avenue for developing and testing complex behaviors.