Pablo Iván Mateos Ramírez

Mr. Pablo Iván Mateos Ramírez

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Research Focus & Metrics

Academic Career Length

3Years (2024-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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22 August 2024 in Applied Sciences
Verified
Journal Article
Open access
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PRPablo Iván Mateos Ramírez
Pablo Iván Mateos Ramírez
JGJavier Gomez
Javier Gomez
CVCarlos Villaseñor
Carlos Villaseñor
Nancy Arana-DanielNancy Arana-Daniel
Nancy Arana-Daniel
In this paper, we present a method for estimating GPS coordinates from visual information captured by a monocular camera mounted on a fixed-wing tactical Unmanned Aerial Vehicle at high altitudes (up to 3000 m) in GPS-denied zones. The main challenge in visual odometry using aerial images is the computation of the scale due to irregularities in the elevation of the terrain. That is, it is not possible to accurately convert from pixels in the image to meters in space, and the error accumulates. The contribution of this work is a reduction in the accumulated error by comparing the images from the camera with satellite images without requiring the dynamic model of the vehicle. The algorithm has been tested in real-world flight experiments at altitudes above 1000 m and in missions over 17 km. It has been proven that the algorithm prevents an increase in the accumulated error.

29 April 2024 in Preprints.org
Verified
Preprint
Open access
PDF file
PRPablo Iván Mateos Ramírez
Pablo Iván Mateos Ramírez
JGJavier Gomez
Javier Gomez
CVCarlos Villaseñor
Carlos Villaseñor
Nancy Arana-DanielNancy Arana-Daniel
Nancy Arana-Daniel
In this paper, we present a method for estimating GPS signals from visual information captured by a monocular camera mounted on a fixed-wing Unmanned Aerial Vehicle. The main challenge in visual odometry from aerial images is the computation of scale due to irregularities in the elevation of the terrain. That is, it is not possible to accurately convert from pixels in the image to meters in space, and the error accumulates. The contribution of this work is to reduce the accumulated error by comparing the images from the camera with satellite images. The algorithm has been tested in real-time experiments, and the results show that it is possible to eliminate the accumulated error using satellite images.