AUTOLAND project: Fixed-wing UAV Landing on a Fast Patrol Boat using Computer Vision

被引:0
作者
Santos, Nuno Pessanha [1 ]
Lobo, Victor [1 ]
Bernardino, Alexandre [2 ]
机构
[1] Portuguese Navy, Portuguese Navy Res Ctr CINAV, P-2810001 Almada, Portugal
[2] Inst Super Tecn IST, Inst Syst & Robot, P-1049001 Lisbon, Portugal
来源
OCEANS 2019 MTS/IEEE SEATTLE | 2019年
关键词
Autonomous Vehicles; Autonomous Landing; Computer Vision; Tracking; Military Vehicles;
D O I
暂无
中图分类号
U6 [水路运输]; P75 [海洋工程];
学科分类号
0814 ; 081505 ; 0824 ; 082401 ;
摘要
The AUTOLAND project main objective was the development of solutions that can enable the autonomous landing of a fixed-wing Unmanned Aerial Vehicle (UAV) on a Fast Patrol Boat (FPB). Since we are operating in a military environment where jamming is possible, we have developed Computer Vision (CV) based systems without using any external sensor information. We have developed and tested two different CV approaches: (i) airborne, and (ii) ground-based. In the airborne approach, the UAV uses its camera and external markers to estimate the relative pose to the landing area and automatically calculates the needed landing trajectory. In the ground-based approach, a ground-based monocular vision system obtains the relative pose of the UAV concerning the camera reference frame using its Computer-Aided Design (CAD) model. Then, a Ground Control Station (GCS) calculates the landing trajectory and transmits it to the UAV. The obtained error was compatible with the automatic landing requirements. The future work will focus on real data acquisition to improve the developed algorithms.
引用
收藏
页数:5
相关论文
共 27 条
[1]  
[Anonymous], INT J MECHATRONICS R
[2]  
[Anonymous], OCEANS 2015 GENOVA
[3]  
Chisholm J. P., 1989, uS Patent, Patent No. [4,866,450, 4866450]
[4]  
Eldridge M., 2009, DESIGN BUILD SEARCH
[5]  
Gajjar B.I., 2004, IFAC Proceedings, V37, P42
[6]  
Gleason ThomasJ., 2010, ENCY AEROSPACE ENG, P1
[7]  
Klausen K, 2016, INT CONF UNMAN AIRCR, P964, DOI 10.1109/ICUAS.2016.7502640
[8]   Monocular vision-based real-time target recognition and tracking for autonomously landing an UAV in a cluttered shipboard environment [J].
Lin, Shanggang ;
Garratt, Matthew A. ;
Lambert, Andrew J. .
AUTONOMOUS ROBOTS, 2017, 41 (04) :881-901
[9]  
Ma J., 2003, INSIDE NAVY, V16, P1
[10]  
McLees R. E., 2018, uS Patent, Patent No. [App. 10/089,892, 10089892]