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On the joint design of routing and scheduling for Vehicle-Assisted Multi-UAV inspection

机译:车辆辅助多无人机巡检的调度与调度联合设计

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摘要

The enabling Internet-of-Things, technology has inspired many innovative sensing platforms. One emerging yet powerful IoT sensing platform is the Unmanned Aerial Vehicle (UAV), which is widely deployed in various fields including photography, inspection, and communications. However, due to limited battery capacities, the hovering time of UAVs is still too short, prohibiting them from undertaking long-range sensing tasks. To accomplish such remote applications, a straightforward solution is to utilize vehicles to carry and launch UAVs. Efficient routing and scheduling for UAVs and vehicles can greatly reduce time consumption and financial expenses incurred in UAV inspection. Nevertheless, previous work in vehicle assisted UAV inspection considered only one UAV, incapable of concurrently serving multiple targets distributed in an area. Employing multiple drones to serve multiple targets in parallel can significantly enhance efficiency and expand service areas. Therefore, in this paper we propose a novel algorithm referred to as joint routing and scheduling algorithm for Vehicle-Assisted Multi-UAV inspection (VAMU), which supports the cooperation of one vehicle and multiple drones for wide area inspection applications. VAMU allows multiple UAVs to be launched and recycled in different locations, minimizing time wastage for both the vehicle and UAVs. Performance evaluation is presented to demonstrate the effectiveness and efficiency of our algorithm when compared with existing solutions. (C) 2018 Elsevier B.V. All rights reserved.
机译:启用的物联网技术启发了许多创新的传感平台。一种新兴但功能强大的物联网传感平台是无人机(UAV),该无人机广泛部署在摄影,检查和通信等各个领域。但是,由于电池容量的限制,无人机的悬停时间仍然太短,无法进行远程感测任务。为了完成这种远程应用,一种直接的解决方案是利用车辆来运载和发射无人机。无人机和车辆的有效路由和调度可以大大减少无人机检查中的时间消耗和财务费用。然而,先前在车辆辅助无人机检查中的工作仅考虑了一种无人机,无法同时服务于分布在一个区域中的多个目标。使用多架无人机并行服务于多个目标可以显着提高效率并扩大服务范围。因此,在本文中,我们提出了一种称为“车辆辅助多UAV检查”(VAMU)的联合路由和调度算法的新颖算法,该算法支持在广域检查应用中单车与多无人机的协作。 VAMU允许在不同位置发射和回收多个无人机,从而最大程度地减少了车辆和无人机的时间浪费。提出了性能评估,以证明与现有解决方案相比我们的算法的有效性和效率。 (C)2018 Elsevier B.V.保留所有权利。

著录项

  • 来源
    《Future generation computer systems》 |2019年第5期|214-223|共10页
  • 作者单位

    Huazhong Univ Sci & Technol, Sch Elect Informat & Commun, Wuhan, Hubei, Peoples R China;

    Huazhong Univ Sci & Technol, Sch Elect Informat & Commun, Wuhan, Hubei, Peoples R China;

    Huazhong Univ Sci & Technol, Sch Elect Informat & Commun, Wuhan, Hubei, Peoples R China;

    Huazhong Univ Sci & Technol, Sch Elect Informat & Commun, Wuhan, Hubei, Peoples R China;

    Huazhong Univ Sci & Technol, Sch Elect Informat & Commun, Wuhan, Hubei, Peoples R China;

    Huazhong Univ Sci & Technol, Sch Elect Informat & Commun, Wuhan, Hubei, Peoples R China;

    Simon Fraser Univ, Sch Comp Sci, Vancouver, BC, Canada;

  • 收录信息 美国《科学引文索引》(SCI);美国《工程索引》(EI);
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    Smart sensing; UAV inspection; Routing; Scheduling; Vehicle-assisted;

    机译:智能感应;无人机检查;选路;调度;车辆辅助;

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