无人机群的连续覆盖问题

Hazim Shakhatreh, Abdallah Khreishah, Jacob Chakareski, H. Salameh, Issa M. Khalil
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引用次数: 64

摘要

无人驾驶飞行器(uav)可用于为受灾地区提供无线网络和远程监视覆盖。在这种情况下,由于无人机的电池容量有限,无人机需要定期返回充电站充电。我们研究了在给定充电需求的情况下,最小化连续覆盖给定区域所需无人机数量的问题。我们证明了这个问题是np完全的。由于其复杂性,我们研究了将覆盖图划分为从充电站开始的循环。我们首先根据充电时间、行驶时间和循环覆盖的子区域数量来表征该循环覆盖的最小无人机数量。在此基础上,提出了一种高效的循环有限能量算法。连续覆盖给定区域的直接方法是将其分成N个子区域,并使用N个额外的无人机进行N次循环覆盖。我们的仿真结果检验了关键系统参数的重要性:无人机的能量容量、覆盖区域的子区域数量以及无人机的充电和飞行时间。我们证明,随着无人机能量容量的增加,与直接方法相比,有限能量循环算法需要的额外无人机减少69%-94%,随着子区域数量的增加,需要的额外无人机减少67%-71%。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
On the continuous coverage problem for a swarm of UAVs
Unmanned aerial vehicles (UAVs) can be used to provide wireless network and remote surveillance coverage for disaster-affected areas. During such a situation, the UAVs need to return periodically to a charging station for recharging, due to their limited battery capacity. We study the problem of minimizing the number of UAVs required for a continuous coverage of a given area, given the recharging requirement. We prove that this problem is NP-complete. Due to its intractability, we study partitioning the coverage graph into cycles that start at the charging station. We first characterize the minimum number of UAVs to cover such a cycle based on the charging time, the traveling time, and the number of subareas to be covered by the cycle. Based on this analysis, we then develop an efficient algorithm, the cycles with limited energy algorithm. The straightforward method to continuously cover a given area is to split it into N subareas and cover it by N cycles using N additional UAVs. Our simulation results examine the importance of critical system parameters: the energy capacity of the UAVs, the number of subareas in the covered area, and the UAV charging and traveling times. We demonstrate that the cycles with limited energy algorithm requires 69%–94% fewer additional UAVs relative to the straightforward method, as the energy capacity of the UAVs is increased, and 67%–71% fewer additional UAVs, as the number of subareas is increased.
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