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兵工学报 ›› 2011, Vol. 32 ›› Issue (11): 1337-1342.

• 论文 • 上一篇    下一篇

不确定环境下的多无人机协同搜索航路规划

吴文超1, 黄长强1, 宋磊1, 唐上钦1, 白壬潮2   

  1. (1. 空军工程大学 工程学院, 陕西 西安 710038; 2. 空军装备部, 北京 100843)
  • 收稿日期:2009-12-30 修回日期:2009-12-30 上线日期:2014-05-04
  • 通讯作者: 吴文超 E-mail:guigui21cn@163.com
  • 作者简介:吴文超(1980—),男,助理工程师,博士研究生
  • 基金资助:
    国家高技术发展计划(2009AAJ205)

Cooperative Search and Path Planning of Multi-unmanned Air Vehicles in Uncertain Environment

WU Wen-chao1,HUANG Chang-qiang1,SONG Lei1,TANG Shang-qin1,BAI Ren-chao2   

  1. (1. College of Engineering, Air Force University of Engineering, Xi’an 710038, Shaanxi, China;2. Air Force Department of Equipment, Beijing 100843, China)
  • Received:2009-12-30 Revised:2009-12-30 Online:2014-05-04
  • Contact: WU Wen-chao E-mail:guigui21cn@163.com

摘要: 为解决多架无人机(UAV)在不确定环境中搜索目标的问题,根据多UAV协同搜索的基本原则,建立了多UAV协同搜索的环境模型和UAV运动模型,提出了一种满足UAV机动限制和适应数据通讯延迟的协同路径决策算法。根据先验知识将环境分为未知环境,已知环境和禁飞区,设计了搜索回报函数,引导UAV对未知环境进行搜索,对已知环境进行规避;提出了禁飞区回避决策,实现了UAV对禁飞区的完全回避。最后进行了仿真实验,并与2种非协同搜索算法的仿真结果进行了比较,结果表明,本文提出的协同搜索算法的有效性。

关键词: 飞行器控制、导航技术, 多无人机, 协同搜索, 航路规划

Abstract: In order to resolve the cooperative search problem of multiple unmanned air vehicles (UAV) in a uncertain environment, this paper presents a basic framework for it first, and then gives the search environment and UAV models. Based on them, a cooperative search path decision for UAV to satisfy the maximum turn radius restriction and communication delay is proposed. According to prior knowledge, the environment can be divided as unknown regions, known regions and prohibited areas, and an award function can be designed for a team of UAVs to search the unknown regions and avoid the known regions. By using an avoidance decision, UAV can get rid of the prohibited area ultimately. Finally, these ideas are simulated and compared with the uncooperative search patterns. The simulation results demonstrate the efficiency of the proposed cooperative approach.

Key words: control and navigation technology of aerocraft, multiple unmanned air vehicles, cooperative search, path planning

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