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Vision-Guided Control Algorithms for Micro Aerial Vehicles

Autorzy
Identyfikatory
Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
This study presents an image analysis method used in the vision guided control system for Micro Air Vehicles (MAVs). The paper describes a hypothetical model of a MAV located in the GPS-denied unknown environment, somewhere indoors. The model keeps moving autonomously following ‘the track’ marked with corners and other feature points recorded with a monocular camera pointed at the far end of a corridor and slightly tilted down at the angle β (20° - 30°). The flight stability and control are provided with an on-board autopilot that maintains zero pitch and roll angles and constant altitude. The image analysis has been based on the real-time computer vision library - OpenCV (Open Source Computer Vision library - http://opencv.willowgarage.com).
Rocznik
Tom
Strony
271–288
Opis fizyczny
Bibliogr. 7 poz., rys.
Twórcy
autor
  • Air Force Institute of Technology
Bibliografia
  • 1. Bołdak C.: Cyfrowe Przetwarzanie Obrazów.
  • 2. Bradski G., Kaehler A.: Learning OpenCV, Computer Vision with the OpenCV library.
  • 3. Celik Koray, Chung Soon-Jo, Clausman M., Somani A.K.: Monocular Vision SLAM forIndoor Aerial Vehicles.
  • 4. Celik Koray, Chung Soon-Jo, Somani A.K.: MVCSLAM: Mono-Vision Corner SLAM for Autonomous Micro-Helicopters in GPS Denied Environments.
  • 5. Harris C., Stephens M.: A combined corner and edge detector: Proceedings of the 4th Alvey Vision Conference, 1988.
  • 6. Hough P.V.C.: Method and means for recognizing complex patterns. U.S. Patent 3,069,654, Dec. 18, 1962.
  • 7. Shi J., Tomasi C.: Good features to track. 9th IEEE Conference on Computer Vision and Pattern Recognition, 1994.
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-f8bbece6-0970-4769-bf94-715dd61d16ad
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