Collaborative Defense with Multiple USVs and UAVs Based on Swarm Intelligence

Xing Wu*, Yuan Liu, Shaorong Xie, Yi-Ke Guo

*Corresponding author for this work

    Research output: Contribution to journalJournal articlepeer-review

    4 Citations (Scopus)

    Abstract

    Modern defense systems are developing towards systematization, intellectualization and automation, which include the collaborative defense system on the sea between multiple unmanned surface vehicles (USVs) and unmanned aerial vehicles (UAVs). UAVs can fly in high altitude and collect marine environment information on patrolling. Furthermore, UAVs can plan defense paths for USVs to intercept intruders with full-assignment or reassignment strategies aiming at maximum overall benefits. Thus, we propose dynamic overlay reconnaissance algorithm based on genetic idea (GI-DORA) to solve the problem of multi-UAV multi-station reconnaissance. Moreover, we develop continuous particle swarm optimization based on obstacle dimension (OD-CPSO) to optimize defense path of USVs to intercept intruders. In addition, under the designed defense constraints, we propose dispersed particle swarm optimization based on mutation and crossover (MC-DPSO) and real-time batch assignment algorithm (RTBA) in emergency for formulating combat defense mission assignment strategy in different scenarios. Finally, we illustrate the feasibility and effectiveness of the proposed methods.

    Original languageEnglish
    Pages (from-to)51-56
    Number of pages6
    JournalJournal of Shanghai Jiaotong University (Science)
    Volume25
    Issue number1
    DOIs
    Publication statusPublished - 1 Feb 2020

    Scopus Subject Areas

    • General

    User-Defined Keywords

    • A
    • collaborative defense
    • mission assignment
    • path planning
    • TP 399
    • unmanned aerial vehicles (UAVs)
    • unmanned surface vehicles (USVs)

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