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EnglishAbstract 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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| Titolo: | Addressing corner detection issues for machine vision based uav aerial refueling |
| Autori: | |
| Data di pubblicazione: | 2007 |
| Rivista: | |
| 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. |
| Handle: | http://hdl.handle.net/11391/38882 |
| Appare nelle tipologie: | 1.1 Articolo in rivista |
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http://hdl.handle.net/11391/38882
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