Overview As a robotic application in artificial intelligence (AI), a social robot is designed for social communication and interactions with humans. Regarding human nature to anthropomorphize objectives, people’s trustworthiness perception towards a social robot is prominent in Human-Robot Interaction (HRI). However, how to achieve a trustworthy looking for social robots is still a challenging problem, this project tries to contribute to this research gap by exploring the meaning of facial anthropomorphic trustworthiness, the effect of specific facial features and their combinations on anthropomorphic trustworthiness, and the effect of dynamic facial features on anthropomorphic trustworthiness under different daily contexts through multidisciplinary approaches. Theoretical contributions and practical implications are discussed in this project.

中文翻译：

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建立“更深层”的信任：通过多学科方法在社交机器人设计中映射人脸拟人的可信度

概述作为人工智能（AI）中的机器人应用程序，社交机器人被设计用于社交交流和与人类的交互。关于人性化目标的人性化，人们对社交机器人的信任感在“人机交互”（HRI）中很突出。然而，如何实现值得信赖的社交机器人寻找仍然是一个具有挑战性的问题，该项目试图通过探索面部拟人可信度的含义，特定面部特征及其组合对拟人可信度的影响以及多学科方法研究动态面部特征在不同日常情况下对拟人可信度的影响。该项目讨论了理论贡献和实践意义。