This paper addresses the design of lightweight radiation sensors for the small-scale unmanned aerial system (UAS) and its implementation for low-altitude radiation source localization and contour mapping. The compact high-resolution gamma-ray CZT sensors were integrated into UAS platforms as plug-and-play components using robot operating system. The swarm of UAS has advantages over a single agent-based approach in detecting radiative sources and effectively mapping the area. The proposed swarm consists of three UAS platforms in a circular formation. The proposed approach can potentially be used for low-altitude clustered environments where a conventional helicopter-based platform cannot be utilized. It can provide a relatively precise boundary of the safe area for potential human exploration as well as enhancing situation awareness capabilities for first responders. The source seeking and contour mapping algorithms are developed based on a simple 1/R² radiation field, but they are validated in more realistic radiation field having multiple sources and physical structures with scattering and attenuation effects simulated by MCNP code. Also, gradient estimation and contour mapping algorithms are validated experimentally with small-scale multicopter platforms in the indoor flight testbed.

中文翻译：

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使用UAS群体的辐射场低空轮廓图

本文介绍了用于小型无人机系统（UAS）的轻型辐射传感器的设计及其在低空辐射源定位和轮廓映射中的实现。紧凑型高分辨率伽马射线CZT传感器使用机器人操作系统作为即插即用组件集成到UAS平台中。与基于单一代理的方法相比，UAS的优势在于可以检测辐射源并有效地绘制区域。拟议中的群体由三个圆形的UAS平台组成。所提出的方法可以潜在地用于不能利用传统的基于直升机的平台的低空集群环境。它可以为潜在的人类探索提供安全区域的相对精确边界，并增强急救人员的态势感知能力。源搜索和轮廓映射算法是基于简单的1 /R ²辐射场，但在具有多个源和物理结构且具有通过MCNP代码模拟的散射和衰减效应的更现实的辐射场中进行了验证。此外，梯度估计和轮廓映射算法已在室内飞行试验台上使用小型多直升机平台进行了实验验证。