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Multi-Agent Cooperative Target Search

机译:多主体合作目标搜索

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摘要

This paper addresses a vision-based cooperative search for multiple mobile ground targets by a group of unmanned aerial vehicles (UAVs) with limited sensing and communication capabilities. The airborne camera on each UAV has a limited field of view and its target discriminability varies as a function of altitude. First, by dividing the whole surveillance region into cells, a probability map can be formed for each UAV indicating the probability of target existence within each cell. Then, we propose a distributed probability map updating model which includes the fusion of measurement information, information sharing among neighboring agents, information decay and transmission due to environmental changes such as the target movement. Furthermore, we formulate the target search problem as a multi-agent cooperative coverage control problem by optimizing the collective coverage area and the detection performance. The proposed map updating model and the cooperative control scheme are distributed, i.e., assuming that each agent only communicates with its neighbors within its communication range. Finally, the effectiveness of the proposed algorithms is illustrated by simulation.
机译:本文研究了一组视觉和协作能力有限的无人飞行器(UAV)对多个移动地面目标进行协作搜索的方法。每个无人机上的机载摄像机视野有限,其目标可分辨性随高度而变化。首先,通过将整个监视区域划分为多个单元,可以为每个UAV形成一个概率图,指示每个单元中目标存在的概率。然后,我们提出了一种分布式概率图更新模型,该模型包括测量信息的融合,相邻代理之间的信息共享,信息衰减以及由于环境变化(例如目标运动)而导致的传输。此外,我们通过优化集体覆盖区域和检测性能,将目标搜索问题表述为多主体协作覆盖控制问题。所提议的地图更新模型和协作控制方案是分布式的,即,假设每个代理仅在其通信范围内与其邻居进行通信。最后,通过仿真说明了所提算法的有效性。

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