Path Planning for Sensor Data Collection by Using UAVs

Baichuan Kong, Hejiao Huang, X. Jia
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引用次数: 3

Abstract

In sparse wireless sensor networks, a UAV is used to collect the sensing data. Each sensor node has a limited transmission range and the UAV has to traverse the transmission range of all sensor nodes to collect data without exhausting energy of the UAV. To minimize the total energy consumption of the UAV on the flying and collecting data, it is essential to consider the tradeoff between path length and data collection time when planning path. In this paper, we show that the optimization problem can be regarded as the traveling salesman problem with neighborhood, which is known to be NP-hard. To address the problem, we decompose it into two subproblems, 1) weighted set cover problem; and 2) a combined optimization problem. Then we solve the first one by a greedy algorithm and the second by an improved shuffled frog-leaping algorithm. We also simulate the proposed algorithm to evaluate its performance.
利用无人机采集传感器数据的路径规划
在稀疏无线传感器网络中,利用无人机采集传感数据。每个传感器节点具有有限的传输距离,无人机必须遍历所有传感器节点的传输距离才能在不耗尽无人机能量的情况下收集数据。为了使无人机在飞行和采集数据时的总能耗最小,在规划路径时必须考虑路径长度和数据采集时间之间的权衡。在本文中,我们证明了优化问题可以看作是具有邻域的旅行商问题,它是已知的NP-hard问题。为了解决这个问题,我们将其分解为两个子问题,1)加权集覆盖问题;2)一个组合优化问题。然后用贪心算法求解第一个问题,用改进的洗牌蛙跳算法求解第二个问题。我们还对所提出的算法进行了仿真,以评估其性能。
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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