系统工程与电子技术

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不确定环境下多无人机协同区域搜索算法

符小卫1, 魏广伟2, 高晓光1   

  1. (1. 西北工业大学电子信息学院, 陕西 西安 710129; 2. 南京电子工程研究所, 江苏 南京 210007)
  • 出版日期:2016-03-25 发布日期:2010-01-03

Cooperative area search algorithm for multi-UAVs in uncertainty environment

FU Xiao-wei1, WEI Guang-wei2, GAO Xiao-guang1   

  1. (1. School of Electronics and Information, Northwestern Polytechnic University, Xi'an 710129, China;
    2. Nanjing Research Institute of Electronic Engineering, Nanjing 210007, China)
  • Online:2016-03-25 Published:2010-01-03

摘要:

针对通信约束在不确定环境下对多无人机协同区域搜索问题的影响,提出了一种基于预测控制思想的多无人机协同区域搜索算法,研究各种通信约束对多无人机协同区域搜索效能的影响。首先,根据多无人机协同搜索的行为准则建立了无人机运动模型和搜索模型。其次,分析了通信约束对于多无人机协同搜索的影响,结合预测控制思想,使多无人机在执行区域搜索任务时同时考虑当前搜索代价和长期搜索代价,提高了多无人机的协同搜索效能。使用蒙特卡罗方法对各种情况进行仿真,仿真结果验证了基于预测控制的多无人机协同区域搜索算法的合理性和有效性。

Abstract:

In order to study the impact of communication constraints on cooperative area search for multi-unmanned aerial vehicle (UAVs) in uncertainty environment, a novel method of multi-UAVs cooperative area search algorithm is presented, which is based on the thoughts of predictive and control. Firstly, the UAV dynamic model and the cooperative search model are established based on the behavior rules of multi-UAVs cooperative search. Secondly, the impact of communication constraints on the multi-UAVs cooperative area search is analyzed. Combined with the predictive and control thoughts, multi-UAVs must consider both the current search cost and future search cost when they carry out the cooperative search mission to improve the cooperative search efficiency of multi-UAVs. The Monte Carlo method is employed to validate the impact of different communication distances and angles on the multi-UAVs cooperative area search. The simulation results show the rationality and validity of the multi-UAVs cooperative area search algorithm.