基于最优路径搜索的无人机装载运输优化问题研究

Research on UAV Loading and Transportation Optimization Based on Optimal Path Search

该文主要研究新型冠状病毒肺炎疫情流行环境下,对小区进行封闭式管理时,利用无人机进行物资运输及体温测量的问题。首先分析主流小区的规模及户型结构数据,筛选出能最具有代表性的小区。对选定小区的住户,在疫情隔离的情况下所需的日常生活用品进行分析,并整理各货品的规格数据,依照整理所得的住户日常生活用品数量及规格数据,根据无人机货舱的尺寸数据,评价分析货物的需求度,建立稳定性模型,进行三维装箱优化。然后根据送货目的地,进行三维空间路径图的坐标系转化,建立最优路径搜索模型,并结合货物的时间需求度对相应目的地进行赋权,转化为带权无向连通图,运用混合粒子群算法进行计算,得出最终的无人机运送路线图。

This paper mainly studies the problems of the use of unmanned aerial vehicles to transport materials and measure body temperature in the enclosed management of the community under the epidemic environment. Firstly, the scale and house type structure data of the mainstream communities are analyzed to select the most representative communities. For selected community residents, in the case of epidemic isolation needed supplies were analyzed, and the daily life and organize the data of the specifications of the goods, in accordance with the number of resident daily life things sorted and specification data, based on the size of the unmanned aerial vehicle hold data, evaluation analysis of goods demand, establish stability model, the three-dimensional packing optimization. Then, according to the delivery destination, coordinate the three-dimensional space path graph, establish the optimal path search model, and combine the time demand degree of the goods to give weight to the corresponding destination, transform it into a weighted undirected connected graph, and use Hybrid Particle Swarm Optimization algorithm to calculate, get the final drone transport roadmap.