Autonomous task allocation for multi-UAV systems based on the locust elastic behavior
Autonomous task allocation for multi-UAV systems based on the locust elastic behavior
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DOI：
10.1016/j.asoc.2018.06.006
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发表时间：
2018-10-01
影响因子：
8.7
通讯作者：
How, Jonathan P.
中科院分区：
文献类型：
--
作者：
Kurdi, Heba A.;Aloboud, Ebtesam;How, Jonathan P.
任务分配是多无人机任务研究和实践者面临的重大挑战。本文提出了一种新的自主生物启发的方法，有效地分配任务之间的多无人机在使命。任务分配由每个UAV基于与个体UAV操作状态和使命参数相关的标准动态地调整，而无需主动参与使命的UAV之间的直接通信。所提出的方法的灵感来自蝗虫物种的性质和他们的自主和弹性的行为，以响应内部和外部的动力。四个长期存在的多无人机任务分配范式，包括拍卖为基础的，最大和，蚁群优化和机会主义的协调计划，用于基准的性能所提出的方法。实验结果表明，新方法大大提高了净吞吐量和平均任务完成时间，同时保持线性运行时间相比，在不同规模的车队规模和任务数的所有基准，表现出更好的可扩展性和可持续性。(C)2018爱思唯尔出版社
Task allocation is a grand challenge facing researches and practitioners in multiple unmanned aerial vehicles (multi-UAVs) missions. This paper proposes a new autonomous bio-inspired approach for efficiently allocating tasks among multiple UAVs during a mission. Task assignments are dynamically adjusted by each UAV on the basis of criteria related to the individual UAV operational status and mission parameters, without direct communication between the UAVs actively taking part in the mission. The proposed approach was inspired by the nature of locust species and their autonomous and elastic behavior in response to inside and outside impetus. Four long-standing multi-UAVs task allocation paradigms, including the auction-based, max-sum, ant colony optimization and opportunistic coordination schemes were used to benchmark the performance of the proposed approach. Experimental results demonstrated that the new approach substantially improves the net throughput and the mean task completion time while maintaining a linear running time when compared to all benchmarks under different scales of fleet size and number of tasks, demonstrating better scalability and sustainability. (C) 2018 Published by Elsevier B.V.