Vision-based Absolute Localization for Unmanned Aerial Vehicles

Aurelien Yol 1 Bertrand Delabarre 1 Amaury Dame 2 Jean-Emile Dartois 3 Eric Marchand 1
1 Lagadic - Visual servoing in robotics, computer vision, and augmented reality
CRISAM - Inria Sophia Antipolis - Méditerranée , Inria Rennes – Bretagne Atlantique , IRISA-D5 - SIGNAUX ET IMAGES NUMÉRIQUES, ROBOTIQUE
3 DiverSe - Diversity-centric Software Engineering
Inria Rennes – Bretagne Atlantique , IRISA-D4 - LANGAGE ET GÉNIE LOGICIEL
Abstract : This paper presents a method for localizing an Unmanned Aerial Vehicle (UAV) using georeferenced aerial images. Easily maneuverable and more and more affordable, UAVs have become a real center of interest. In the last few years, their utilization has significantly increased. Today, they are used for multiple tasks such as navigation, transportation or vigilance. Nevertheless, the success of these tasks could not be possible without a highly accurate localization which can, unfortunately be often laborious. Here we provide a multiple usage localization algorithm based on vision only. However, a major drawback with vision-based algorithms is the lack of robustness. Most of the approaches are sensitive to scene variations (like season or environment changes) due to the fact that they use the Sum of Squared Differences (SSD). To prevent that, we choose to use the Mutual Information (MI) which is very robust toward local and global scene variations. However, dense approaches are often related to drift disadvantages. Here, we solve this problem by using georeferenced images. The localization algorithm has been implemented and experimen- tal results are presented demonstrating the localization of a hexarotor UAV fitted with a downward looking camera during real flight tests.
Type de document :
Communication dans un congrès
IEEE/RSJ Int. Conf. on Intelligent Robots and Systems, IROS'14, Sep 2014, Chicago, United States. 2014
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  • HAL Id : hal-01010140, version 1

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Aurelien Yol, Bertrand Delabarre, Amaury Dame, Jean-Emile Dartois, Eric Marchand. Vision-based Absolute Localization for Unmanned Aerial Vehicles. IEEE/RSJ Int. Conf. on Intelligent Robots and Systems, IROS'14, Sep 2014, Chicago, United States. 2014. 〈hal-01010140〉

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