UAV Task Assignment Algorithm Based on Splitting and Reorganization

2019 IEEE International Conferences on Ubiquitous Computing & Communications (IUCC) and Data Science and Computational Intelligence (DSCI) and Smart Computing, Networking and Services (SmartCNS) Pub Date : 2019-10-01 DOI:10.1109/IUCC/DSCI/SmartCNS.2019.00035

Jiehong Wu, Xin Su

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Abstract

With the development of e-commerce, one of the essential ways of logistics distribution in the future is the distribution by UAVs. The limitations of the UAVs' resources and the distribution of express delivery need to be considered when delivery multiple merchandises. If the UAV task assignment is only based on the location of the delivery point, more UAVs are needed to accomplish the task. Therefore, it is necessary to divide the merchandises at the same distribution point. The goal of this paper is to use the minimum number of UAVs while minimizing the total distance traveled. This paper considers the two constraints of the maximum payload and cruising range of the UAV and models it according to these two constraints. Then the group-split-reorganize method is proposed to separate the packets that meet the constraints and optimize the intragroup path. Finally, experiments confirmed the feasibility and effectiveness of the method.

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基于分割重组的无人机任务分配算法

随着电子商务的发展，无人机配送是未来物流配送的重要方式之一。在投递多种商品时，需要考虑无人机资源和快递配送的局限性。如果无人机的任务分配仅仅基于送货点的位置，则需要更多的无人机来完成任务。因此，有必要在同一分销点划分商品。本文的目标是使用最少数量的无人机，同时使总飞行距离最小化。本文考虑了无人机的最大载荷和巡航距离这两个约束条件，并根据这两个约束条件对无人机进行了建模。在此基础上，提出了组分裂-重组方法，分离满足约束条件的分组，优化组内路径。最后，通过实验验证了该方法的可行性和有效性。

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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来源期刊

2019 IEEE International Conferences on Ubiquitous Computing & Communications (IUCC) and Data Science and Computational Intelligence (DSCI) and Smart Computing, Networking and Services (SmartCNS)

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