UAV safe route planning based on PSO-BAS algorithm

被引:0
|
作者
ZHANG Honghong [1 ,2 ]
GAN Xusheng [1 ,2 ]
LI Shuangfeng [1 ,2 ]
CHEN Zhiyuan [1 ]
机构
[1] Air Traffic Control and Navigation College, Air Force Engineering University
[2] National Key Laboratory of Air Traffic Collision Prevention
基金
中国国家自然科学基金;
关键词
D O I
暂无
中图分类号
TP18 [人工智能理论]; V279 [无人驾驶飞机];
学科分类号
081104 ; 0812 ; 0835 ; 1111 ; 1405 ;
摘要
In order to solve the current situation that unmanned aerial vehicles(UAVs) ignore safety indicators and cannot guarantee safe operation when operating in low-altitude airspace, a UAV route planning method that considers regional risk assessment is proposed. Firstly, the low-altitude airspace is discretized based on rasterization, and then the UAV operating characteristics and environmental characteristics are combined to quantify the risk value in the low-altitude airspace to obtain a 3D risk map. The path risk value is taken as the cost, the particle swarm optimization-beetle antennae search(PSO-BAS) algorithm is used to plan the spatial 3D route, and it effectively reduces the generated path redun dancy. Finally, cubic B-spline curve is used to smooth the plan ned discrete path. A flyable path with continuous curvature and pitch angle is generated. The simulation results show that the generated path can exchange for a path with a lower risk value at a lower path cost. At the same time, the path redundancy is low, and the curvature and pitch angle continuously change. It is a flyable path that meets the UAV performance constraints.
引用
收藏
页码:1151 / 1160
页数:10
相关论文
共 50 条
  • [1] UAV safe route planning based on PSO-BAS algorithm
    Zhang Honghong
    Gan Xusheng
    Li Shuangfeng
    Chen Zhiyuan
    [J]. JOURNAL OF SYSTEMS ENGINEERING AND ELECTRONICS, 2022, 33 (05) : 1151 - 1160
  • [2] A Kind of Route Planning Method for UAV Based on Improved PSO Algorithm
    Geng, Qingbo
    Zhao, Zheng
    [J]. 2013 25TH CHINESE CONTROL AND DECISION CONFERENCE (CCDC), 2013, : 2328 - 2331
  • [3] 3D route planning for UAV based on improved PSO algorithm
    Fang, Qun
    Xu, Qing
    [J]. Xibei Gongye Daxue Xuebao/Journal of Northwestern Polytechnical University, 2017, 35 (01): : 66 - 73
  • [4] On route-planning of UAV based on discrete PSO and voronoi diagram
    Peng Jianliang
    Zhu Fan
    Sun Xiuxia
    Sun Biao
    [J]. PROCEEDINGS OF THE 26TH CHINESE CONTROL CONFERENCE, VOL 5, 2007, : 804 - +
  • [5] Route Planning of UAV Based On Improved GSO Algorithm
    Zheng Zixuan
    Yuan Jianping
    [J]. 2014 INTERNATIONAL CONFERENCE ON MECHANICAL ENGINEERING AND AUTOMATION (ICMEA), 2014, : 242 - 247
  • [6] Route Planning of UAV Based on Improved Ant Colony Algorithm
    Qian, Zhengxiang
    Wang, Guocheng
    Wang, Jingen
    Shi, Yongxin
    [J]. PROCEEDINGS OF THE INTERNATIONAL CONFERENCE ON LOGISTICS, ENGINEERING, MANAGEMENT AND COMPUTER SCIENCE (LEMCS 2015), 2015, 117 : 1421 - 1426
  • [7] Route Planning Algorithm of Region Important Target Search Based on PSO
    Tang Shu-juan
    Zhao Ke
    Li De-fang
    Wang Nan
    [J]. 2018 IEEE 4TH INTERNATIONAL CONFERENCE ON CONTROL SCIENCE AND SYSTEMS ENGINEERING (ICCSSE 2018), 2018, : 545 - 548
  • [8] Three-Dimensional Path Planning for UAV Based on Improved PSO Algorithm
    Wang, Qiang
    Zhang, An
    Qi, Linghui
    [J]. 26TH CHINESE CONTROL AND DECISION CONFERENCE (2014 CCDC), 2014, : 3981 - 3985
  • [9] AGRICULTURAL UAV CROP SPRAYING PATH PLANNING BASED ON PSO-A* ALGORITHM
    Fan, Lijuan
    [J]. INMATEH-AGRICULTURAL ENGINEERING, 2023, 71 (03): : 625 - 636
  • [10] Research on route planning for solar UAV based on the intelligent optimization algorithm
    Hu, Zhonghua
    Liu, Shihao
    [J]. SCIENCE PROGRESS, 2023, 106 (03)