We investigate estimating a human's world belief state using a robot's observations in a dynamic, 3D, and partially observable environment. The methods are grounded in mental model theory, which posits that human decision making, contextual reasoning, situation awareness, and behavior planning draw from an internal simulation or world belief state. When in teams, the mental model also includes a team model of each teammate's beliefs and capabilities, enabling fluent teamwork without the need for constant and explicit communication. In this work we replicate a core component of the team model by inferring a teammate's belief state, or level one situation awareness, as a human-robot team navigates a household environment. We evaluate our methods in a realistic simulation, extend to a real-world robot platform, and demonstrate a downstream application of the belief state through an active assistance semantic reasoning task.

翻译：我们研究利用机器人在动态、三维且部分可观测环境中的观测估计人类的世界信念状态。该方法基于心理模型理论，该理论认为人类的决策制定、情境推理、态势感知和行为规划均源于内部模拟或世界信念状态。在团队协作中，心理模型还包含对每个队友信念与能力的团队模型，从而使团队无需持续显式沟通即可实现流畅协作。在本工作中，我们通过推断队友的信念状态——即一级态势感知——复制了团队模型的核心组成部分，以支持人机团队在家庭环境中的导航任务。我们在仿真环境与真实机器人平台上验证了该方法，并通过主动辅助语义推理任务展示了信念状态的下游应用。