论文标题
彼此了解：校准意图，能力和对人机合作的信任
Getting to Know One Another: Calibrating Intent, Capabilities and Trust for Human-Robot Collaboration
论文作者
论文摘要
共同的经验表明，彼此了解良好的代理商可以更好地合作。在这项工作中，我们解决了人类机器人协作中校准意图和能力的问题。特别是，我们专注于机器人试图帮助无法直接传达其意图的人类的场景。此外，两个代理商可能具有彼此未知的不同功能。我们采用了一种决策理论方法，并建议使用相关的在线求解器进行TICC-POMDP进行建模。实验表明，我们的方法在模拟和对人类受试者的现实研究中都可以提高团队表现。
Common experience suggests that agents who know each other well are better able to work together. In this work, we address the problem of calibrating intention and capabilities in human-robot collaboration. In particular, we focus on scenarios where the robot is attempting to assist a human who is unable to directly communicate her intent. Moreover, both agents may have differing capabilities that are unknown to one another. We adopt a decision-theoretic approach and propose the TICC-POMDP for modeling this setting, with an associated online solver. Experiments show our approach leads to better team performance both in simulation and in a real-world study with human subjects.
