物联网学报

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一种针对无人机配送网络的能量自维持调度方案

徐佳 1,2，袁鸣 1，吴思徐 1，谭芯 1，骆健 1,2   

  1. 1.南京邮电大学计算机学院，江苏 南京 210023；
    2.南京邮电大学江苏省大数据安全与智能处理重点实验室，江苏 南京 210023
  • 作者简介:徐佳（1980— ），男，博士，南京邮电大学教授，主要研究方向为群智感知、无线充电、边缘计算和区块链等。 袁鸣（1997— ），女，南京邮电大学计算机学院硕士生，主要研究方向为路径规划和无线充电。 吴思徐（1997— ），男，南京邮电大学计算机学院博士生，主要研究方向为无线充电传感器网络。 谭芯（1998— ），女，南京邮电大学计算机学院硕士生，主要研究方向为边缘计算。 骆健（1976— ），女，硕士，南京邮电大学副教授，主要研究方向为数据挖掘和机器学习。

An energy self-sustaining scheduling scheme for UAV delivery networks

XU Jia1,2，YUAN Ming1，WU Sixu1，TAN Xin1，LUO Jian1,2   

  1. 1.School of Computer Science, Nanjing University of Posts and Telecommunications, Nanjing
    210023, China
    2.Jiangsu Key Laboratory of Big Data Security and Intelligent Processing, Nanjing University of 
    Posts and Telecommunications, Nanjing 210023, China

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摘要： 近年来，快递行业需求快速增长，物流配送行业压力剧增。无人机配送凭借其人力成本低、灵活方便等特性成为车辆配送的有益补充。然而，无人机配送受到续航能力和负载能力等因素的制约，需要低成本且能量自维持的配送和充电调度方案来支持多无人机的协同配送。本文提出了两阶段的能量自维持的多无人机协同配送及充电调度方案。第一阶段在考虑满足无人机载重和能量约束的前提下，最小化完成区域内所有配送任务所需的无人机数量，并给出对应配送路线。提出了无人机配送调度算法(UDSA，UAV delivery schedulingalgorithm)，并从理论上证明 UDSA 的近似度。第二阶段对具有不同到达时间的无人机进行充电调度，最小化所有无人机的最大充电完成时间。提出了一个具有近似度的无人机充电调度算法(UCSA，UAV charging scheduling algorithm)来求解该问题。仿真实验结果表明，与基准算法相比，UDSA 最多可以减少 44.17%的无人机数量；UCSA 最多可以减少 18.87%的最大充电完成时间。

关键词: 无人机, 配送调度, 车辆路由问题, 无线充电调度

Abstract: In recent years, the demand of express industry has increased rapidly, and the express industry is under increasing pressure. The Unmanned Aerial Vehicle (UAV) delivery has become a effective supplement to vehicle delivery due to its low human cost, flexibility and convenience. However, UAVs are often limited by endurance and load capacity, A low cost and energy self-sustaining scheduling scheme for delivery and charging is needed. This paper proposes a two-stage self-sustaining multiple UAV cooperative delivery and charging scheduling scheme. The first stage, aims to find the delivery routes of UAVs to complete all delivery tasks in the region such that the number of UAVs is minimized under the load capacity and energy constraints of UAVs. The UAV Delivery Scheduling Algorithm (UDSA) is proposed, and the approximation of UDSA is proved theoretically. The second stage aims to schedule the charging of UAVs with different arrival times to minimize the maximum charging completion time of all UAVs. An approximate UAV Delivery Scheduling Algorithm (UCSA) is proposed to solve the problem. The simulation results show that, compared with the benchmark algorithm, UDSA can reduce the number of UAVs by 44.17% at most, and UCSA can reduce the maximum charging completion time by 18.87% at most.

Key words:  UAV, delivery scheduling, vehicle routing problem, wireless charging scheduling

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