Maintaining connectivity in UAV swarm sensing

W. L. Teacy, Jing Nie, S. McClean, G. Parr
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引用次数: 43

Abstract

In many applications, Unmanned Aerial Vehicles (UAVs) provide an indispensable platform for gathering information about the situation on the ground. However, to maximise information gained about the environment, such platforms require increased autonomy to coordinate the actions of multiple UAVs. This has led to the development of flight planning and coordination algorithms designed to maximise information gain during sensing missions. However, these have so far neglected the need to maintain wireless network connectivity. In this paper, we address this limitation by enhancing an existing multi-UAV planning algorithm with two new features that together make a significant contribution to the state-of-the-art: (1) we incorporate an on-line learning procedure that enables UAVs to adapt to the radio propagation characteristics of their environment, and (2) we integrate flight path and network routing decisions, so that modelling uncertainty and the affect of UAV position on network performance is taken into account.
无人机群传感中的连通性维护
在许多应用中,无人驾驶飞行器(uav)为收集地面情况信息提供了不可或缺的平台。然而,为了最大限度地获取有关环境的信息,这样的平台需要增加自主权来协调多个无人机的行动。这导致了飞行计划和协调算法的发展,旨在最大限度地提高传感任务期间的信息增益。然而,到目前为止,这些都忽略了保持无线网络连接的需要。在本文中,我们通过增强现有的多无人机规划算法来解决这一限制,该算法具有两个新特征,它们共同对最先进的技术做出了重大贡献:(1)我们纳入了一个在线学习过程,使无人机能够适应其环境的无线电传播特性;(2)我们集成了飞行路径和网络路由决策,因此建模不确定性和无人机位置对网络性能的影响被考虑在内。
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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