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Multi-UAV surveillance implementation under hierarchical dynamic task scheduling architecture

基于层次式动态任务调度架构下的多无人机巡逻实现

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Abstract

In this paper, we consider a multi-UAV surveillance scenario where a team of unmanned aerial vehicles (UAVs) synchronously covers an area for monitoring the ground conditions. In this scenario, we adopt the leader-follower control mode and propose a modified Lyapunov guidance vector field (LGVF) approach for improving the precision of surveillance trajectory tracking. Then, in order to adopt to poor communication conditions, we propose a prediction-based synchronization method for keeping the formation consistently. Moreover, in order to adapt the multi-UAV system to dynamic and uncertain environment, this paper proposes a hierarchical dynamic task scheduling architecture. In this architecture, we firstly classify all the algorithms that perform tasks according to their functions, and then modularize the algorithms based on plugin technology. Afterwards, integrating the behavior model and plugin technique, this paper designs a three-layer control flow, which can efficiently achieve dynamic task scheduling. In order to verify the effectiveness of our architecture, we consider a multi-UAV traffic monitoring scenario and design several cases to demonstrate the online adjustment from three levels, respectively.

摘要

本文考虑了一个多无人机巡逻的场景。在该场景中, 一组无人机同步对一片地面区域进行覆盖 巡逻。采用领航者-跟随者控制模式, 并提出了一种改进的李雅普诺夫向量场方法以提高轨迹跟踪的 精度。为了适应通信条件差的情况, 提出了一种基于预测的同步方法来保持编队的一致性。此外, 为 了使多无人机系统能够适应动态和不确定环境, 提出了一种层次式动态任务调度架构。在该架构中, 首先对所有执行任务的算法按其功能进行分类, 然后基于插件技术对算法进行模块化。通过结合行为 模型和插件技术, 设计了三层控制流, 以有效实现任务的动态调度。为了验证所提出架构的有效性, 考虑了一个多无人机交通监视场景, 并设计实验从三层控制流方面展示动态任务调度的效果。

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Authors and Affiliations

  1. State Key Laboratory of High Performance Computing (HPCL), College of Computer, National University of Defense Technology, Changsha, 410073, China

    Wen-di Wu  (伍文迪) & Yu-hua Tang  (唐玉华)

  2. Artificial Intelligence Research Center (AIRC), National Innovation Institute of Defense Technology (NIIDT), Beijing, 100071, China

    Yun-long Wu  (武云龙), Xiao-guang Ren  (任小广) & Dian-xi Shi  (史殿习)

  3. Tianjin Artificial Intelligence Innovation Center (TAIIC), Tianjin, 300457, China

    Yun-long Wu  (武云龙), Jing-hua Li  (李晶华), Xiao-guang Ren  (任小广) & Dian-xi Shi  (史殿习)

Authors
  1. Wen-di Wu  (伍文迪)
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  2. Yun-long Wu  (武云龙)
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  3. Jing-hua Li  (李晶华)
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  4. Xiao-guang Ren  (任小广)
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  5. Dian-xi Shi  (史殿习)
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  6. Yu-hua Tang  (唐玉华)
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Corresponding authors

Correspondence to Yun-long Wu  (武云龙) or Xiao-guang Ren  (任小广).

Additional information

Foundation item

Project(2017YFB1301104) supported by the National Key Research and Development Program of China; Projects(61906212, 61802426) supported by the National Natural Science Foundation of China

Contributors

The overarching research goals were developed by WU Wen-di, WU Yun-long, REN Xiao-guang and TANG Yu-hua. WU Wen-di and WU Yun-long conducted the literature review and wrote the first draft of the manuscript. LI Jing-hua analyzed the calculated results. SHI Dian-xi edited the draft of manuscript.

Conflict of interest

WU Wen-di, WU Yun-long, LI Jing-hua, REN Xiao-guang, SHI Dian-xi, and TANG Yu-hua declare that they have no conflict of interest.

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Wu, Wd., Wu, Yl., Li, Jh. et al. Multi-UAV surveillance implementation under hierarchical dynamic task scheduling architecture. J. Cent. South Univ. 27, 2614–2627 (2020). https://doi.org/10.1007/s11771-020-4486-8

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  • DOI: https://doi.org/10.1007/s11771-020-4486-8

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