标题： 不确定性强健的机器人助手机器人主动意图识别 显示英文标题

标题： Uncertainty-Resilient Active Intention Recognition for Robotic Assistants

摘要： 在机器人助手中实现有目的的行为需要整合多个组件和技术进步。 通常，问题会被简化为识别明确的提示，这限制了自主性，或者通过假设（如近乎完美的信息）被过度简化。 我们认为，仍存在一个关键的空白——即关于人类意图识别中固有的不确定结果和感知误差的推理挑战。 作为回应，我们提出了一种框架，该框架旨在抵御不确定性和传感器噪声，将实时传感器数据与多种规划器相结合。 以意图识别的POMDP为中心，我们的方法在不确定性下解决了合作规划和行动问题。 我们的综合框架已在物理机器人上成功测试，并取得了有前景的结果。 显示英文摘要

摘要： Purposeful behavior in robotic assistants requires the integration of multiple components and technological advances. Often, the problem is reduced to recognizing explicit prompts, which limits autonomy, or is oversimplified through assumptions such as near-perfect information. We argue that a critical gap remains unaddressed -- specifically, the challenge of reasoning about the uncertain outcomes and perception errors inherent to human intention recognition. In response, we present a framework designed to be resilient to uncertainty and sensor noise, integrating real-time sensor data with a combination of planners. Centered around an intention-recognition POMDP, our approach addresses cooperative planning and acting under uncertainty. Our integrated framework has been successfully tested on a physical robot with promising results.