Adaptive Multiple Task Assignments for UAVs Using Discrete Particle Swarm Optimization

被引：12
|
作者：
Chen, Kun [1 ]
Sun, Qibo [1 ]
Zhou, Ao [1 ]
Wang, Shangguang [1 ]
机构：
[1] Beijing Univ Posts & Telecommun, State Key Lab Networking & Switching Technol, Beijing, Peoples R China
来源：
INTERNET OF VEHICLES: TECHNOLOGIES AND SERVICES TOWARDS SMART CITY (IOV 2018) | 2018年 / 11253卷
基金：
北京市自然科学基金;
关键词：
UAV; Forest firefighting; Task assignment; Particle swarm optimization; AERIAL VEHICLES;
D O I：
10.1007/978-3-030-05081-8_16
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
The forest fire is an extremely dangerous natural disaster. The traditional fire-fighting equipment have great difficulty in performing firefighting in mountain terrain. Unmanned aerial vehicles (UAVs) are coming into a popular form in forest firefighting. In view of the suddenness of forest fires, the adaptive and dynamic firefighting task assignment for UAV is of great significance, and the current firefighting task assignment cannot address this issue. This paper proposed an adaptive and dynamic multiple task assignment method for UAVs. Firstly, the adaptive and dynamic firefighting task assignment is formulated as an optimization problem. Secondly, an assignment algorithm is proposed to solve the problem by extending the particle swarm optimization (PSO) algorithm. Finally, the experiment results verify the effectiveness of the proposed algorithm.
引用
收藏
页码：220 / 229
页数：10
相关论文
共 50 条
  • [21] A modified particle swarm optimization using adaptive strategy
    Liu, Hao
    Zhang, Xu-Wei
    Tu, Liang-Ping
    EXPERT SYSTEMS WITH APPLICATIONS, 2020, 152
  • [22] Adaptive particle swarm optimization using velocity feedback
    Iwasaki, Nobuhiro
    Yasuda, Keiichiro
    INTERNATIONAL JOURNAL OF INNOVATIVE COMPUTING INFORMATION AND CONTROL, 2005, 1 (03): : 369 - 380
  • [23] Convex combination multiple populations competitive swarm optimization for moving target search using UAVs
    Ma, Tianxi
    Wang, Yunhe
    Li, Xiangtao
    INFORMATION SCIENCES, 2023, 641
  • [24] Locating multiple optima using particle swarm optimization
    Brits, R.
    Engelbrecht, A. P.
    van den Bergh, F.
    APPLIED MATHEMATICS AND COMPUTATION, 2007, 189 (02) : 1859 - 1883
  • [25] An Efficient Algorithm of Discrete Particle Swarm Optimization for Multi-Objective Task Assignment
    Qiao, Nannan
    You, Jiali
    Sheng, Yiqiang
    Wang, Jinlin
    Deng, Haojiang
    IEICE TRANSACTIONS ON INFORMATION AND SYSTEMS, 2016, E99D (12): : 2968 - 2977
  • [26] An Analysis for Particle Trajectories of a Discrete Particle Swarm Optimization
    Tao, Qian
    Chang, Hui-you
    Yi, Yang
    Gu, Chun-qin
    Li, Wen-jie
    ICCSIT 2010 - 3RD IEEE INTERNATIONAL CONFERENCE ON COMPUTER SCIENCE AND INFORMATION TECHNOLOGY, VOL 4, 2010, : 293 - 298
  • [27] Improved Particle Swarm Optimization Algorithm for Cooperative Task Assignment of Multiple vehicles
    Wang L.
    Xu C.
    Li M.
    Zhao H.
    Binggong Xuebao/Acta Armamentarii, 2023, 44 (08): : 2224 - 2232
  • [28] Adaptive particle swarm optimization algorithms
    Ai, The Jin
    Kachitvichyanukul, Voratas
    PROCEEDINGS OF THE 4TH INTERNATIONAL CONFERENCE ON INTELLIGENT LOGISTICS SYSTEMS, 2008, : 460 - 469
  • [29] A Particle Swarm Optimization-Based Cooperation Method for Multiple-Target Search by Swarm UAVs in Unknown Environments
    Gupta, Aniket
    Virmani, Aman
    Mahajan, Parth
    Nallanthigal, Raghava
    2021 7TH INTERNATIONAL CONFERENCE ON AUTOMATION, ROBOTICS AND APPLICATIONS (ICARA 2021), 2021, : 95 - 100
  • [30] Performance Analysis of Adaptive Beamforming using Particle Swarm Optimization
    Banerjee, Smita
    Dwivedi, Ved Vyas
    2016 11TH INTERNATIONAL CONFERENCE ON INDUSTRIAL AND INFORMATION SYSTEMS (ICIIS), 2016, : 242 - 246
12345