Toward developing an optimal cooperative search algorithm for multiple Unmanned Aerial Vehicles

被引:5
|
作者
DeLima, Pedro [1 ]
Pack, Daniel [1 ]
机构
[1] USAF Acad, Dept Elect & Comp Engn, Colorado Springs, CO 80840 USA
关键词
cooperative; unmanned aerial vehicles; search algorithm; autonomous; decentralized;
D O I
10.1109/CTS.2008.4543971
中图分类号
TP3 [计算技术、计算机技术];
学科分类号
0812 ;
摘要
In search and surveillance operations, a team of small Unmanned Aerial Vehicles (UAVs) can provide a robust solution that surpasses in efficiency what can be achieved by a single aircraft with comparatively superior mobility and sensors. The key to unlock such potential is in cooperative decentralized control strategies that allow each UAV to independently determine its actions while aiming at optimizing the team's objectives through collaboration. In this paper we present the results of a statistical analysis that demonstrates the efficacy of the distributed search technique proposed by the authors in [1]. Three metrics are used to measure the search performance: dynamic coverage, heterogeneity of the coverage, and energy consumption.
引用
收藏
页码:506 / 512
页数:7
相关论文
共 50 条
  • [1] Cooperative Search by Multiple Unmanned Aerial Vehicles in a Nonconvex Environment
    Ji, Xiaoting
    Wang, Xiangke
    Niu, Yifeng
    Shen, Lincheng
    [J]. MATHEMATICAL PROBLEMS IN ENGINEERING, 2015, 2015
  • [2] A Cooperative Search and Coverage Algorithm with Controllable Revisit and Connectivity Maintenance for Multiple Unmanned Aerial Vehicles
    Liu, Zhong
    Gao, Xiaoguang
    Fu, Xiaowei
    [J]. SENSORS, 2018, 18 (05)
  • [3] Optimal Cooperative Thermalling of Unmanned Aerial Vehicles
    Klesh, Andrew T.
    Kabamba, Pierre T.
    Girard, Anouck R.
    [J]. OPTIMIZATION AND COOPERATIVE CONTROL STRATEGIES, 2009, 381 : 355 - 369
  • [4] Optimal Search for Marine Target Using Multiple Unmanned Aerial Vehicles
    Yao, Peng
    Wang, Xiaodong
    Yi, Ke
    [J]. 2018 37TH CHINESE CONTROL CONFERENCE (CCC), 2018, : 4552 - 4556
  • [5] Optimal cooperative path planning of unmanned aerial vehicles by a parallel genetic algorithm
    Shorakaei, Hamed
    Vahdani, Mojtaba
    Imani, Babak
    Gholami, Ali.
    [J]. ROBOTICA, 2016, 34 (04) : 823 - 836
  • [6] Optimal scheduling for aerial recovery of multiple unmanned aerial vehicles using genetic algorithm
    Liu, Yongbei
    Qi, Naiming
    Yao, Weiran
    Liu, Yanfang
    Li, Yuan
    [J]. PROCEEDINGS OF THE INSTITUTION OF MECHANICAL ENGINEERS PART G-JOURNAL OF AEROSPACE ENGINEERING, 2019, 233 (14) : 5347 - 5359
  • [7] COOPERATIVE TASK PLANNING FOR MULTIPLE UNMANNED AERIAL VEHICLES USING A GENETIC ALGORITHM
    Geng, L.
    Zhang, Y. F.
    Wang, J. J.
    Fuh, Jerry Y. H.
    Teo, S. H.
    [J]. CONTROL AND INTELLIGENT SYSTEMS, 2014, 42 (02) : 119 - 125
  • [8] Distributed Cooperative Search Algorithm With Task Assignment and Receding Horizon Predictive Control for Multiple Unmanned Aerial Vehicles
    Hou, Kun
    Yang, Yajun
    Yang, Xuerong
    Lai, Jiazhe
    [J]. IEEE ACCESS, 2021, 9 : 6122 - 6136
  • [9] An Optimal Routing Algorithm for Unmanned Aerial Vehicles
    Kim, Sooyeon
    Kwak, Jae Hyun
    Oh, Byoungryul
    Lee, Da-Han
    Lee, Duehee
    [J]. SENSORS, 2021, 21 (04) : 1 - 15
  • [10] A self-organized search and attack algorithm for multiple unmanned aerial vehicles
    Gao, Chen
    Zhen, Ziyang
    Gong, Huajun
    [J]. AEROSPACE SCIENCE AND TECHNOLOGY, 2016, 54 : 229 - 240