Global Path Planning Of Fixed-wing UAV Based On Improved RRT* Algorithm

被引:3
作者
Jiang, Xiangju [1 ]
Huang, Bingde [1 ]
机构
[1] Lanzhou Jiaotong Univ, Sch automat & Elect Engn, Lanzhou 730070, Peoples R China
来源
JOURNAL OF APPLIED SCIENCE AND ENGINEERING | 2023年 / 26卷 / 10期
基金
中国国家自然科学基金;
关键词
Fixed-wing UAV; RRT* algorithm; Path planning; B-spline curve;
D O I
10.6180/jase.202310_26(10).0009
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
Aiming at the problems that RRT* algorithm has poor directionality in path planning and the path is not sufficient for UAV flight, an improved RRT* algorithm is proposed by analyzing the kinematics model of fixed-wing UAV. Firstly, the sampling function is introduced to make the random tree grow towards the target point, which improves the efficiency of path search. Secondly, the expansion of algorithm nodes is constrained according to the flight dynamics of fixed-wing UAV, and then b-spline curve is used to optimize the path suitable for UAV flight. Finally, the feasibility of the algorithm is verified in two-dimensional and three-dimensional environments. The simulation results show that the improved RRT* algorithm greatly reduces the time cost of path planning and is a fast and effective global path planning algorithm.
引用
收藏
页码:1441 / 1450
页数:10
相关论文
共 14 条
[1]  
[陈秋莲 Chen Qiulian], 2019, [计算机工程与应用, Computer Engineering and Application], V55, P10
[2]   Mixed population RRT algorithm for UAV path planning [J].
Gao, Sheng ;
Ai, Jianliang ;
Wang, Zhihao .
Xi Tong Gong Cheng Yu Dian Zi Ji Shu/Systems Engineering and Electronics, 2020, 42 (01) :101-107
[3]  
Ge JH, 2020, INT CONF INFO SCI, P44, DOI [10.1109/icist49303.2020.9202213, 10.1109/ICIST49303.2020.9202213]
[4]   基于改进RRT-Connect算法的移动机器人路径规划 [J].
黄壹凡 ;
胡立坤 ;
薛文超 .
计算机工程, 2021, 47 (08) :22-28
[5]   UAV Track Planning of Electric Tower Pole Inspection Based on Improved Artificial Potential Field Method [J].
Jiang, Xiangju ;
Deng, Ye .
JOURNAL OF APPLIED SCIENCE AND ENGINEERING, 2021, 24 (02) :123-132
[6]   Optimal Kinodynamic Motion Planning using Incremental Sampling-based Methods [J].
Karaman, Sertac ;
Frazzoli, Emilio .
49TH IEEE CONFERENCE ON DECISION AND CONTROL (CDC), 2010, :7681-7687
[7]  
Lee D, 2014, INT C CONTR AUTOMAT, P835, DOI 10.1109/ICCAS.2014.6987895
[8]   Collision-free Path Planning for UAVs using Efficient Artificial Potential Field Algorithm [J].
Selvam, Praveen Kumar ;
Raja, Gunasekaran ;
Rajagopal, Vasantharaj ;
Dev, Kapal ;
Knorr, Sebastian .
2021 IEEE 93RD VEHICULAR TECHNOLOGY CONFERENCE (VTC2021-SPRING), 2021,
[9]  
[王闯 Wang Chuang], 2019, [控制工程, Control Engineering of China], V26, P1466
[10]   Dynamic path planning using anytime repairing sparse A * algorithm [J].
Wang S. ;
Long T. ;
Wang Z. ;
Cai Q. .
Xi Tong Gong Cheng Yu Dian Zi Ji Shu/Systems Engineering and Electronics, 2018, 40 (12) :2714-2721