Vision-Based Geolocation Tracking System for Uninhabited Aerial Vehicles

被引:15
|
作者
Campbell, Mark E. [1 ]
Wheeler, Matthew [2 ]
机构
[1] Cornell Univ, Sibley Sch Mech & Aerosp Engn, Ithaca, NY 14853 USA
[2] Insitu Grp, Bingen, WA 98605 USA
关键词
D O I
10.2514/1.44013
中图分类号
V [航空、航天];
学科分类号
08 ; 0825 ;
摘要
The design and implementation of a vision-based geolocation tracking system for uninhabited aerial vehicles is described. The geolocation tracking system for the uninhabited aerial vehicles includes avionics, a gimballing camera with feedback isolation and command loops, and aground station. The point of interest is locked in the camera image by maintaining the center of the image frame to frame. An architecture for a geolocation tracking estimator is developed and demonstrated. The estimator has the unique characteristics of being modular so that it can work with different camera systems and different avionics components, compensate for random and bias uncertainties, run in real time, and deliver a consistent estimate of the location and uncertainty of the object being tracked. Flight results using the SeaScan uninhabited aerial vehicles show consistent results for two- and three-dimensional tracking of stationary and moving targets.
引用
收藏
页码:521 / 532
页数:12
相关论文
共 50 条
  • [41] Robust vision-based tau control method for unmanned aerial vehicles
    Liu J.
    Wu W.
    Zhang Y.
    Li J.
    [J]. Liu, Jintao (liu_jintao@126.com), 1600, Editorial Board of Journal of Harbin Engineering (37): : 192 - 197and230
  • [42] Vision-based obstacle avoidance for flapping-wing aerial vehicles
    Fu, Qiang
    Yang, Yuhang
    Chen, Xiangyang
    Shang, Yalin
    [J]. SCIENCE CHINA-INFORMATION SCIENCES, 2020, 63 (07)
  • [43] Vision-based Detection and Pose Estimation for Formation of Micro Aerial Vehicles
    Zhang, Mengmi
    Lin, Feng
    Chen, Ben M.
    [J]. 2014 13TH INTERNATIONAL CONFERENCE ON CONTROL AUTOMATION ROBOTICS & VISION (ICARCV), 2014, : 1473 - 1478
  • [44] Vision-Based Hardware-in-the-Loop-Simulation for Unmanned Aerial Vehicles
    Khoa Dang Nguyen
    Ha, Cheolkeun
    [J]. INTELLIGENT COMPUTING THEORIES AND APPLICATION, PT I, 2018, 10954 : 72 - 83
  • [45] Vision-based obstacle avoidance for flapping-wing aerial vehicles
    Qiang FU
    Yuhang YANG
    Xiangyang CHEN
    Yalin SHANG
    [J]. Science China(Information Sciences), 2020, 63 (07) : 119 - 121
  • [46] Monocular Vision-Based Obstacle Detection/Avoidance for Unmanned Aerial Vehicles
    Al-Kaff, Abdulla
    Meng, Qinggang
    Martin, David
    de la Escalera, Arturo
    Maria Armingol, Jose
    [J]. 2016 IEEE INTELLIGENT VEHICLES SYMPOSIUM (IV), 2016, : 92 - 97
  • [47] Vision-Based Navigation Techniques for Unmanned Aerial Vehicles: Review and Challenges
    Arafat, Muhammad Yeasir
    Alam, Muhammad Morshed
    Moh, Sangman
    [J]. DRONES, 2023, 7 (02)
  • [48] Automation of Industrial Vehicles: A Vision-based Line Tracking Application
    Armesto, L.
    Tornero, J.
    [J]. 2009 IEEE CONFERENCE ON EMERGING TECHNOLOGIES & FACTORY AUTOMATION (EFTA 2009), 2009,
  • [49] Observation Modelling for Vision-Based Target Search by Unmanned Aerial Vehicles
    Teacy, W. T. Luke
    Julier, Simon J.
    De Nardi, Renzo
    Rogers, Alex
    Jennings, Nicholas R.
    [J]. PROCEEDINGS OF THE 2015 INTERNATIONAL CONFERENCE ON AUTONOMOUS AGENTS & MULTIAGENT SYSTEMS (AAMAS'15), 2015, : 1607 - 1614
  • [50] Vision-Based Sense-and-Avoid Framework for Unmanned Aerial Vehicles
    Huh, Sungsik
    Cho, Sungwook
    Jung, Yeondeuk
    Shim, David Hyunchul
    [J]. IEEE TRANSACTIONS ON AEROSPACE AND ELECTRONIC SYSTEMS, 2015, 51 (04) : 3427 - 3439