无人机危险品集装箱堆场巡查路径优化研究

发布时间：2018-05-07 15:04

  本文选题：无人机巡逻 + 模拟退火　； 参考：《铁道科学与工程学报》2017年11期

【摘要】：针对危险品集装箱堆场的巡逻问题,提出使用无人机进行危险品集装箱堆场巡逻的方法,通过和车辆路径CVRP问题的类比,得到优化后的无人机路径。该方法是在传统扫描算法的基础之上,提出一种全扫描的方法,使用模拟退火算法不断求出无人机当前阶段的飞行距离,再将该距离与无人机的额定航程进行对比,直到求得的距离大于无人机航程时,扫描停止,并将该点除去,保留之前的点和路径,形成一条无人机的飞行路径。最后通过和传统方式的比较,得出使用无人机巡逻可以比人工巡逻节省73.33%的时间,节约66.21%运营成本。
[Abstract]:Aiming at the patrol problem of dangerous goods container yard, the method of using UAV to patrol dangerous goods container yard is put forward. The optimized UAV path is obtained by analogy with CVRP problem of vehicle path. Based on the traditional scanning algorithm, a full scan method is proposed in this paper. The simulated annealing algorithm is used to continuously calculate the flying distance of UAV at present stage, and then the distance is compared with the rated range of UAV. When the distance obtained is larger than the range of the UAV, the scan stops and the point is removed, and the previous points and paths are retained to form a flight path of the UAV. Finally, by comparing with the traditional method, it is concluded that using UAV patrol can save 73.33% of time and 66.21% of operating cost than manual patrol.
【作者单位】： 上海海事大学物流研究中心;工业互联网创新中心(上海)有限公司;
【基金】：国家自然科学基金资助项目(71471109) 2017年上海海事大学研究生创新基金资助项目(2017YCX025) 工业互联网综合实验床平台基金资助项目(ZN2016020109)
【分类号】：U698.5
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本文编号：1857394