Vision-Guided Control Algorithms for Micro Aerial Vehicles

• Autorzy: Wijaszka, M.
• 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).

Słowa kluczowe

EN

vision guided control; computer vision; OpenCV vision systems; micro air vehicle (MAV)

• Czasopismo: Prace Naukowe Instytutu Technicznego Wojsk Lotniczych
• Rocznik: 2013
• Tom: nr 33
• Strony: 271–288
• Opis fizyczny: Bibliogr. 7 poz., rys.

Twórcy

autor

Wijaszka, M.

• 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.

Identyfikatory

DOI

10.2478/afit-2013-0016