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大规模无线传感网络数据收集的无人机路径规划

DOI: 10.15918/j.tbit1001-0645.2015.10.011

Keywords: 大规模 人机 路径规划 旅行商问题 网格划分

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Abstract:

针对部署在地表交通困难的大规模线传感网络,采用目前可控人机(unmanned aerial vehicles, UAV)进行数据收集能够达到更好的效果. 然而,考虑到人机自身有限的资源,以及网络中存在大量传感器节点的情况,人机飞行路径规划对于顺利完成数据收集任务具有重要作用. 人机路径规划可以看作经典的旅行商问题(traveling salesman problem,TSP). 针对部署具有均匀性特点的大规模线传感网络,提出了一种规则化快速路径规划(fast path planning with rules, FPPWR)算法. 该算法通过网格划分,将全局区域飞行路径的求解划分到多个较小的方格中进行,并通过成对算子路径优化算法在初等飞行路径上将方格区域中的路径合并为全局路径. 实验证明,该算法在保证了较高精度的同时,显著提升了路径规划的效率

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