This paper describes the results of the analysis of specific 'corner detection' algorithms within a machine vision approach for the problem of aerial refueling for unmanned aerial vehicles. Specifically, the performances of the SUSAN and the Harris corner detection algorithms have been compared. A critical goal of this study was to evaluate the interface of these feature extraction schemes with the successive detection and labeling, and pose estimation schemes in the overall scheme. Closed-loop simulations were performed using a Simulink-based simulation environment to reproduce docking maneuvers using the US Air Force refueling boom.
Addressing corner detection issues for machine vision based UAV aerial refueling
Aspekte der Erkennung von Eckpunkten bei der Betankung unbemannter Flugzeuge auf Basis des maschinellen Sehens
Machine Vision and Applications ; 18 , 5 ; 261-273
2007
13 Seiten, 14 Bilder, 2 Tabellen, 20 Quellen
Article (Journal)
English
Addressing corner detection issues for machine vision based UAV aerial refueling
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