Gas Source Localization Based on Binary Sensing with a UAV

T. Wiedemann, M. Schaab, J. M. Gomez, D. Shutin, M. Scheibe, A. Lilienthal
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引用次数: 3

Abstract

Precise gas concentration measurements are often difficult, especially by in-situ sensors mounted on an Unmanned Aerial Vehicle (UAV). Simple gas detection, on the other hand, is more robust and reliable, yet brings significantly less information for gas source localization. In this paper, we compensate for the lack of information by a physical model of gas propagation based on the advection-diffusion Partial Differential Equation (PDE). By linking binary gas detection measurements to computed gas concentration using the physical model and an appropriately designed likelihood function, it becomes possible to identify the most likely gas source distribution. The approach was validated in two experiments with ethanol and smoke as “toy” gasses. It is shown that the method is able to successfully localize the source locations in experiments based on gas detection measurements taken by a UAV.
基于二值感知的无人机气源定位
精确的气体浓度测量通常是困难的,特别是安装在无人驾驶飞行器(UAV)上的原位传感器。另一方面,简单的气体检测方法鲁棒性和可靠性更高,但为气源定位提供的信息明显较少。在本文中,我们通过基于平流-扩散偏微分方程(PDE)的气体传播物理模型来弥补信息的不足。通过使用物理模型和适当设计的似然函数将二元气体检测测量与计算的气体浓度联系起来,可以确定最可能的气源分布。该方法在两个实验中得到了验证,乙醇和烟雾作为“玩具”气体。实验结果表明,该方法能够在无人机气体检测测量的基础上成功地定位出气体源的位置。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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