AUTOMATIC ESTIMATION OF ALTITUDE OF THE REFERENCES POINTS FOR AERIAL AUTONOMOUS NAVIGATION USING AERIAL PHOTOGRAPHS AND CHARACTERISTIC POINTS
| Autor: | E. H. Shiguemori, M.A. P. Domiciano, L. A. V. Dias |
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| Rok vydání: | 2014 |
| Předmět: |
Altitude (triangle)
Aerial survey Zernike polynomials business.industry Satellite navigation system ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION Scale-invariant feature transform symbols.namesake Geography Position (vector) symbols Computer vision Artificial intelligence Digital elevation model business Inertial navigation system |
| Zdroj: | Proceedings of 10th World Congress on Computational Mechanics. |
| ISSN: | 2358-0828 |
| DOI: | 10.5151/meceng-wccm2012-19168 |
| Popis: | The use of computer vision techniques to solve problems related to estimation of position has increased in recent decades due to rapid technological and computing develop- ment. This paper presents an approach to obtain position information of an Unmanned Aerial Vehicle (UAV) based on aerial images. The problem addressed is to allow a UAV to be locat- ed above ground. The considered vehicle has an inertial navigation system (INS) and receives no assistance of a satellite navigation system. Due to the inherent errors of the INS that cause disorientation of the UAV, an image-tracking system is proposed. The proposed methodology has been to build, in real-time and embedded, a Digital Elevation Model of reference points (DEM-R) to allow a vehicle to locate in the ground based on the comparison between this and pre-existing model. In order to achieve this objective it is necessary to identify similar points in sequential images and calculate the altitude of these points. This enables build the DEM-R. We used the SIFT techniques and Zernike moments to identify similar points. We used aerial imagery of the city of Sao Jose dos Campos - Sao Paulo - Brazil, with longitudinal coverage of 60%. The obtained results show that the methodology is viable to the proposed problem, autonomous navigation of UAVs. |
| Databáze: | OpenAIRE |
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