Cooperative Area Search for Multiple UAVs based on RRT and Decentralized Receding Horizon Optimization

被引:0
|
作者
Peng, Hui [1 ]
Su, Fei [1 ]
Bu, Yanlong [1 ]
Zhang, Guozhong [1 ]
Shen, Lincheng [1 ]
机构
[1] Natl Univ Def Technol, Sch Mech Engn & Automat, Changsha 410073, Peoples R China
关键词
D O I
暂无
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
This paper presents a decentralized method to the problem of multiple Unmanned Aerial Vehicles (UAVs) cooperative search of an unknown area. Firstly, based on search map model, the multiple UAVs cooperative search problem is posed as a receding horizon (RH) optimization decision problem, and a RH based UAV search decision process is proposed. Then, this centralized on-line optimization problem is partitioned into several UAV subsystems optimization problems and solved in a parallel manner using a Nash optimality based decentralized RH optimization method, and Particle Swarm Optimization (PSO) is used for subsystem optimization. Next, by introducing the heuristic information and improving the extension of node, a modified Rapidly-exploring Random Tree (RRT) based path planning algorithm is presented to the UAV search path planning. It is shown by simulation that the proposed method can reduce the size of multiple UAVs optimization decision problem, and lead to an efficient cooperative search for multiple UAVs.
引用
收藏
页码:298 / 303
页数:6
相关论文
共 50 条
  • [21] Hierarchical Decentralized Receding Horizon Control of Multiple Vehicles with Communication Failures
    Izadi, Hojjat A.
    Gordon, Brandon W.
    Zhang, Youmin
    [J]. IEEE TRANSACTIONS ON AEROSPACE AND ELECTRONIC SYSTEMS, 2013, 49 (02) : 744 - 759
  • [22] Cooperative Search Method for Multiple UAVs Based on Deep Reinforcement Learning
    Gao, Mingsheng
    Zhang, Xiaoxuan
    [J]. SENSORS, 2022, 22 (18)
  • [23] A MPC and genetic algorithm based approach for multiple UAVs cooperative search
    Tian, J
    Zheng, YX
    Zhu, HY
    Shen, LC
    [J]. COMPUTATIONAL INTELLIGENCE AND SECURITY, PT 1, PROCEEDINGS, 2005, 3801 : 399 - 404
  • [24] A Study on the Receding Horizon Guidance with the Sequence Optimization for the Terminal Area
    Toratani, Daichi
    Ueno, Seiya
    Higuchi, Takehiro
    [J]. 2014 PROCEEDINGS OF THE SICE ANNUAL CONFERENCE (SICE), 2014, : 1742 - +
  • [25] Cooperative Distributed Robust Trajectory Optimization Using Receding Horizon MILP
    Kuwata, Yoshiaki
    How, Jonathan P.
    [J]. IEEE TRANSACTIONS ON CONTROL SYSTEMS TECHNOLOGY, 2011, 19 (02) : 423 - 431
  • [26] A Study on the receding horizon guidance with the sequence optimization for the terminal area
    20144800261641
    [J]. (1) Graduate School of Environment and Information Sciences, Yokohama National University, Yokohama, Japan; (2) Reserch Institute of Environment and Information Sciences, Yokohama National University, Yokohama, Japan, 1600, (Society of Instrument and Control Engineers (SICE), United States):
  • [27] Decentralized receding horizon control with communication bandwidth allocation for multiple vehicle systems
    Izadi, H. A.
    Gordon, B. W.
    Rabbath, C. A.
    [J]. OPTIMAL CONTROL APPLICATIONS & METHODS, 2012, 33 (01): : 1 - 22
  • [28] Cooperative receding horizon path planning of multiple robots by genetic algorithm
    Jiang Zhengxiong
    Jia Qiuling
    Li Guangwen
    [J]. ISTM/2007: 7TH INTERNATIONAL SYMPOSIUM ON TEST AND MEASUREMENT, VOLS 1-7, CONFERENCE PROCEEDINGS, 2007, : 2758 - 2761
  • [29] 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
  • [30] Cooperative Receding Horizon Path Planning of Multiple Robots by Genetic Algorithm
    Li, Guangwen
    Jia, Qiuling
    [J]. 2008 IEEE INTERNATIONAL CONFERENCE ON AUTOMATION AND LOGISTICS, VOLS 1-6, 2008, : 2449 - 2453