A Multi-UAV Cooperative Searching Method Based on Differential Evolution

被引:1
作者
Ma, Caibei [1 ,2 ]
Zhu, Xiaozhou [2 ]
Liu, Sherigyang [2 ]
Gui, Jialijun [2 ]
Yao, Wen [2 ]
机构
[1] Natl Univ Def Technol, Coll Aerosp Sci & Engn, Changsha 410073, Peoples R China
[2] Chinese Acad Mil Sci, Def Innovat Inst, Beijing 100071, Peoples R China
来源
2022 34TH CHINESE CONTROL AND DECISION CONFERENCE, CCDC | 2022年
基金
美国国家科学基金会;
关键词
Unmanned Aerial Vehicle(UAV); cooperative search; uncertain environment; differential evolution; path planning;
D O I
10.1109/CCDC55256.2022.10034399
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Cooperative search of multiple UAVs in uncertain environments is a hotspot of cooperative control of multiple UAVs. The purpose of multi-UAVs cooperative search is to obtain the information of the search area, reduce the uncertainty of the environment, and find the hidden target in the environment as much as possible. The searching efficiency of the traditional methods is low, the linearity of the fitness function makes the algorithm easy to converge locally. To solve this problem, a multi-UAV cooperative region search algorithm based the differential evolution algorithm is proposed. Firstly, the searching probability map is established to describe the uncertainty of the search environment. Then, the cooperative searching path of multi-UAVs is generated by the proposed algorithm. Finally, the simulation results verify the effectiveness of the method that the strategy obtain a better coverage of the high-value area.
引用
收藏
页码:5643 / 5648
页数:6
相关论文
共 50 条
  • [1] Multi-UAV Cooperative Coverage Search for Various Regions Based on Differential Evolution Algorithm
    Zeng, Hui
    Tong, Lei
    Xia, Xuewen
    BIOMIMETICS, 2024, 9 (07)
  • [2] Reinforcement Learning based Approach for Multi-UAV Cooperative Searching in Unknown Environments
    Yue, Wei
    Guan, Xianhe
    Xi, Yun
    2019 CHINESE AUTOMATION CONGRESS (CAC2019), 2019, : 2018 - 2023
  • [3] A composite differential evolution algorithm for multi-UAV cooperative dynamic target search
    Zhou H.-X.
    Xu Y.
    Luo D.-L.
    Kongzhi yu Juece/Control and Decision, 2023, 38 (11): : 3128 - 3136
  • [4] Multi-UAV Cooperative Searching and Tracking for Moving Targets Based on Multi-Agent Reinforcement Learning
    Su, Kai
    Qian, Feng
    APPLIED SCIENCES-BASEL, 2023, 13 (21):
  • [5] An Improved Potential Game Theory Based Method for Multi-UAV Cooperative Search
    Ni, Jianjun
    Tang, Guangyi
    Mo, Zhengpei
    Cao, Weidong
    Yang, Simon X.
    IEEE ACCESS, 2020, 8 : 47787 - 47796
  • [6] Q-Learning-based Multi-UAV Cooperative Path Planning Method
    Yin Y.
    Wang X.
    Zhou J.
    Binggong Xuebao/Acta Armamentarii, 2023, 44 (02): : 484 - 495
  • [7] Pigeon-inspired optimisation-based cooperative target searching for multi-UAV in uncertain environment
    Luo, Delin
    Li, Sijie
    Shao, Jiang
    Xu, Yang
    Liu, Yong
    INTERNATIONAL JOURNAL OF BIO-INSPIRED COMPUTATION, 2022, 19 (03) : 158 - 168
  • [8] Cooperative Area Coverage Reconnaissance Method for Multi-UAV System
    Long, Guoqing
    Zhu, Xiaoping
    MANUFACTURING SCIENCE AND TECHNOLOGY, PTS 1-8, 2012, 383-390 : 4141 - +
  • [9] Distributed cooperative search methods of multi-UAV based on prediction of moving targets
    Qi, Xiao-Ming
    Wei, Rui-Xuan
    Shen, Dong
    Ru, Chang-Jian
    Zhou, Huan
    Xi Tong Gong Cheng Yu Dian Zi Ji Shu/Systems Engineering and Electronics, 2014, 36 (12): : 2417 - 2425
  • [10] Multi-UAV cooperative search on region division and path planning
    Dai J.
    Xu F.
    Chen Q.
    Hangkong Xuebao/Acta Aeronautica et Astronautica Sinica, 2020, 41