EAGER: Model-Driven Sensor Management in Support of Decision Making

想象一下非法核材料可能在运输途中的情景。我们怎么能在几分钟内判断出一辆卡车、一艘船、一节火车车厢，甚至是拥挤的街道上一个背着背包的人是否是放射性物质的携带者（可能是屏蔽的）？该项目侧重于通过配备辐射计数器的操纵机器人（地面和/或空中）从远处及时探测弱放射源问题背后的基本科学。所提出的理论通过提供改进的决策算法来促进国家安全目标。这些算法可以支持现有的和未来的传感器技术，并有助于开发新的检测工具，可以形成一个有效的保护层，以防止国内的放射性攻击，并有助于一个有用的工具，核不扩散abroad.Novel功能的方法在这个项目中包括基于模型的方法，主动传感，以及以与现实世界场景更兼容的方式来制定检测问题。该方法通过查询测量模型而不是仅仅查询测量数据，从而从经典的主动感知方法出发，以提高决策的性能。该方法标志着传感器管理中主动感测的范式转变：而不是依靠传感器测量（数据）来决定如何采样，这里的方法是依靠测量物理（模型）。

Imagine a scenario in which illicit nuclear material may be in transit. How can we tell in a matter of minutes whether a truck, boat, railway car, or even a person with a backpack in a crowed street is a carrier of (possibly shielded) radioactive material? This project focuses on the underlying science behind the problem of timely detection of weak radioactive sources from a distance, by steering robots (ground and/or aerial) equipped with radiation counters. The proposed theory promotes national security objectives by providing improved decision-making algorithms. These algorithms can support both existing and future sensor technology, and help develop new detection tools which can form an effective layer of protection against radiological attacks at home, and contribute a useful tool for nuclear nonproliferation abroad.Novel features of the methodology in this project include the model-based approach to active sensing, and the formulation of the detection problem in a way that is more compatible with real-world scenarios. This approach departs from the classical active sensing approaches by querying measurement models, as opposed to merely measurement data, in order to improve the performance of decision making. The approach signifies a paradigm shift for active sensing in sensor management: instead of relying on sensor measurements (data) to decide how to sample, here the approach is to rely on measurement physics (models).