HCC: Medium: Proactive Physical Assistance for Collaborative Human-Robot Teams

与人并肩工作的机器人必须能够提供物理帮助。 然而，机器人还没有主动提供帮助。相反，他们通常遵循预设的协作计划，或者只在用户明确请求帮助时才做出响应。 虽然这种反应式方法在许多情况下都很有用，但它不太适合许多协作应用程序。该项目的重点是使机器人能够主动提供及时、适合任务并为其人类伙伴所需的物理帮助。 我们的目标是建造能够回答三个关键问题的机器人：（1）队友需要帮助吗？(2)我（或其他人）可以帮忙吗？（3）我应该帮忙吗？ 通过启用这些功能，该项目将使协作的人类-机器人团队更流畅，更有效地运作。为了开发这些能力，将推进三个自然交织在一起但捕获这些任务的重要计算方面的研究重点。首先，通过机器人的心理理论感知其他智能体。该研究小组将开发计算模型，这些模型源于我们对人类如何代表他人的知识，信仰和愿望的理解，以保持人类和机器人队友的精神状态的上下文敏感模型。 第二，规划支持性行动。 该团队将构建一个系统，通过使用机器人自身能力的训练模型沿着确定这些行动是否对团队有价值的预测规划系统，生成机器人可以采取的可能的支持行动，以帮助队友。 第三，群体动态中的决策。该机器人将监测和参与支持其合作伙伴的整体动态的社会活动，包括传统的对话界面和促进协作的更微妙的社会机制。该奖项反映了NSF的法定使命，并通过使用基金会的智力价值和更广泛的影响审查标准进行评估，被认为值得支持。

It is essential that robots working side-by-side with people be able to offer physical assistance. However, robots do not yet take the initiative to help. Instead, they typically follow preset plans for collaboration, or respond only when users explicitly ask for help. While useful in many situations, this reactive approach is poorly suited for many collaborative applications. This project focuses on enabling robots to proactively offer physical assistance that is timely, task-appropriate, and wanted by their human partners. The goal is to construct robots that can answer three key questions: (1) Does a teammate need help? (2) Can I (or someone else) help? and (3) Should I help? By enabling these capabilities, this project will make collaborative human-robot teams function more fluently and efficiently. To develop these capabilities, three research thrusts that are naturally intertwined but that capture important computational aspects of these tasks, will be advanced. First, perceiving other agents through a Theory of Mind for robots. The research team will develop computational models derived from our understanding of how humans represent the knowledge, beliefs, and desires of others to maintain context-sensitive models of the mental states of human and robotic teammates. Second, planning for supportive actions. The team will construct a system that generates possible supportive actions that the robot could take to help a teammate by using a trained model of the robot's own capabilities along with a predictive planning system that determines if these actions have value to the team. Third, decision making within the dynamics of a group. The robot will monitor and engage in social activities that support the overall dynamics of its partners including both conventional conversational interfaces and more subtle social mechanisms that facilitate collaboration.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.