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High Resolution Atmospheric Sensing Using UAVs

机译:高分辨率大气感测使用无人机

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摘要

A technique to obtain high resolution atmospheric data using small mobile sensors is presented. A fluid based control scheme using smoothed particle hydrodynamics (SPH) is implemented to perform field measurements in a leader-follower arrangement for a team of unmanned aerial vehicles (UAVs) equipped with environmental sensors. A virtual leader is created by using a reduced density SPH particle to guide the unmanned aerial vehicles along a desired path. Simulations using the control scheme demonstrate excellent measurement ability, swarm coherence, and leader following capability for large swarms. A K-means algorithm is used to reduce the measurement error and provide accurate interpolation of the field measurement data. Experimental results are presented which demonstrate the guidance and collision avoidance properties of the control scheme using real UAVs. Readings from the UAV's temperature and humidity sensor suite are used with the K-means algorithm to produce a smooth estimation of the respective distribution fields.
机译:提出了使用小型移动传感器获得高分辨率大气数据的技术。实施使用平滑粒子流体动力学(SPH)的流体基于流体的控制方案,以在配备有环境传感器的无人航空车辆(无人机)的团队中对领导者 - 跟随装置进行现场测量。通过使用减小的密度SPH粒子来创建虚拟领导者,以沿着所需路径引导无人驾驶飞行器。使用控制方案的模拟展示了大型群体的能力之后的出色测量能力,群体一致性和领导者。 K-Means算法用于减少测量误差并提供现场测量数据的精确插值。提出了实验结果,展示了使用真实无人机的控制方案的引导和碰撞性能。 UAV的温度和湿度传感器套件的读数与K-Means算法一起使用,以产生相应的分配字段的平滑估计。

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