基于无人机的全息成像和计算机视觉的大气气溶胶诊断
Atmospheric aerosol diagnostics with UAV-based holographic imaging and computer vision
摘要：
排放到大气中的颗粒物对于表征颗粒大小、形态和成分等特性至关重要，有助于更好地了解对公众健康和气候的影响。然而，目前还没有能够在与野火或火山爆发等事件相关的广泛领域内以如此高的细节测量单个颗粒的技术。为了解决这个问题，我们提出了一个自主的测量系统，涉及一个无人驾驶飞行器（UAV）加上一个数字内联全息显微镜原位粒子诊断。飞行控制系统使用计算机视觉来定位并跟踪载有颗粒的流动的运动，同时对颗粒进行采样，以确定它们从源头运输时的特性。我们证明了该系统适用于测量烟羽中的颗粒物，并讨论了这种类型的系统在类似应用中的更广泛的影响。
英文摘要：
Emissions of particulate matter into the atmosphere are essential to characterize, in terms of properties such as particle size, morphology, and composition, to better understand impacts on public health and the climate. However, there is no currently available technology capable of measuring individual particles with such high detail over the extensive domains associated with events such as wildfires or volcanic eruptions. To solve this problem, we present an autonomous measurement system involving an unmanned aerial vehicle (UAV) coupled with a digital inline holographic microscope for in situ particle diagnostics. The flight control uses computer vision to localize and then trace the movements of particle-laden flows while sampling particles to determine their properties as they are transported away from their source. We demonstrate this system applied to measuring particulate matter in smoke plumes and discuss broader implications for this type of system in similar applications.
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