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Adaptive Gas Source Localization Strategies and Gas Distribution Mapping using a Gas-sensitive Micro-Drone

机译:使用气敏微无人机的自适应气体源定位策略和气体分配映射

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In this paper we exemplify how to address environmental monitoring tasks with a gas-sensitive micro-drone and present two different approaches to locate gas emission sources. First, we sent the micro-drone in real-world experiments along predefined sweeping trajectories to model the gas distribution. The identification of the gas source location is made afterwards based on the created model. Second, we adapted two bio-inspired plume tracking algorithms that have been implemented so far on ground-based mobile robots. We developed a third bio-inspired algorithm, which is called "pseudo gradient-based algorithm", and compared its perfomance in real-world experiments with the other two algorithms.
机译:在本文中,我们举例说明如何用气敏微无人机解决环境监测任务,并提出两种不同的方法来定位气体排放源。首先,我们在现实世界实验中沿着预定义的扫描轨迹派出了微无人机,以模拟气体分布。基于所产生的模型之后,使气体源位置的识别。其次,我们改编了两台生物启发的羽流跟踪算法,该算法已经在基于地面的移动机器人上实施。我们开发了第三种生物启发算法,称为“基于伪梯度的算法”,并将其与其他两种算法的实际实验中的性能进行了比较。

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