Approches déterministes et bayésiennes pour un suivi robuste : application à l'asservissement visuel d'un drone

Céline Teulière 1, 2
2 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
Abstract : For a robot to autonomously localise or position itself with respect to its environ- ment, a key requirement is the perception of this environment. In this respect, the visual information provided by a camera is a particularly rich source of information, commonly used in robotics. Our work deals with the use of visual information in the context of UAV control. More speciﰀcally, two tasks have been considered : ﰀrst, a tracking task, in which a UAV has to follow a moving object - a car - in an unknown environment, second, a positioning task for a UAV navigating in a structured GPS-deprived environment. In both cases, we propose full approaches, considering both the robust extraction of appropriate visual informations and the visual servoing of the UAV. The experi- ments performed on a small quadrotor UAV show the validity of our approaches.
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Céline Teulière. Approches déterministes et bayésiennes pour un suivi robuste : application à l'asservissement visuel d'un drone. Automatique / Robotique. Université Rennes 1, 2010. Français. ⟨tel-00589519⟩

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