UAV Autonomous landing algorithm based on machine vision

被引:0
作者
Xu, Cheng [1 ]
Tang, Yuanheng [2 ]
Liang, Zuotang [2 ]
Yin, Hao [2 ]
机构
[1] Army Engn Univ, Xuzhou 221004, Jiangsu, Peoples R China
[2] Naval Aeronaut Univ, Qingdao 266041, Shandong, Peoples R China
来源
PROCEEDINGS OF 2018 IEEE 4TH INFORMATION TECHNOLOGY AND MECHATRONICS ENGINEERING CONFERENCE (ITOEC 2018) | 2018年
关键词
unmanned aerial vehicle; vision navigation; pose estimation; autonomous landing; machine vision;
D O I
暂无
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Autonomous landing capability is very important for UAV, this paper presentes a UAV landing method based on visual navigation pose parameters calculateion. The navigation algorithm is based on monocular vision, and the shape and size parameters of land objects need to be carefully designed. The contour extraction method is combined with the Angle detection method to obtain 8 Angle points with good geometric distribution and moderate number. The algorithm can calculate the relative pose parameters of the UAV and the landing platform accurately by only using these 8 Angle points without the need of depth information. The 8 angular points extracted are directly used as the input of detection and tracking, which ensures the real-time performance of the algorithm and reduces the processing time of stable tracking landmarks. Finally, the real-time calculation of the flight pose parameters is carried out. The results show that the algorithm has an average period of 49.523 ms(about 20 fps) and can meet the real-time requirements of autonomous landing visual navigation when the speed is not higher than 2m/s.
引用
收藏
页码:824 / 829
页数:6
相关论文
共 11 条
[1]   Airborne Vision-Based Navigation Method for UAV Accuracy Landing Using Infrared Lamps [J].
Gui, Yang ;
Guo, Pengyu ;
Zhang, Hongliang ;
Lei, Zhihui ;
Zhou, Xiang ;
Du, Jing ;
Yu, Qifeng .
JOURNAL OF INTELLIGENT & ROBOTIC SYSTEMS, 2013, 72 (02) :197-218
[2]  
Kong W, INT ROB SYST IROS 20
[3]  
Laiacker M, 2013, IEEE INT C INT ROBOT, P2971, DOI 10.1109/IROS.2013.6696777
[4]  
Niu Haitao, 2011, Infrared Laser Engineering, V40, P133
[5]   On-Board Dual-Stereo-Vision for the Navigation of an Autonomous MAV [J].
Schauwecker, Konstantin ;
Zell, Andreas .
JOURNAL OF INTELLIGENT & ROBOTIC SYSTEMS, 2014, 74 (1-2) :1-16
[6]  
Sharp CS, 2001, IEEE INT CONF ROBOT, P1720, DOI 10.1109/ROBOT.2001.932859
[7]  
Tsai AC, 2006, LECT NOTES COMPUT SC, V4319, P672
[8]  
Wu Xian-Liang, 2010, J SYSTEM SIMULATION, V22, P62
[9]   Research on computer vision-based for UAV autonomous landing on a ship [J].
Xu, Guili ;
Zhang, Yong ;
Ji, Shengyu ;
Cheng, Yuehua ;
Tian, Yupeng .
PATTERN RECOGNITION LETTERS, 2009, 30 (06) :600-605
[10]  
Xu Yong, 2015, LASER OPTOELECTRONIC, V52, P160