Abstract This paper describes the results of the analysis of specific ‘corner detection’ algorithms within a MachineVision 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

FRAVOLINI, Mario Luca;
2007

Abstract

Abstract This paper describes the results of the analysis of specific ‘corner detection’ algorithms within a MachineVision 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.
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/11391/38882
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