Accéder directement au contenu Accéder directement à la navigation
Autre publication

Detecting and avoiding frontal obstacles from monocular camera for micro unmanned aerial vehicles

Abstract : There exists a lot of work in the literature trying to make the UAVs fly autonomously for example extracting perspective cues such as straight lines. However, it is only available in well-defined human made environments, in addition to many other cues which require enough texture information. Our main target is to detect and avoid frontal obstacles from a monocular camera using a quad rotor Ar.Drone 2 by exploiting optical flow as a motion parallax, the drone is permitted to fly at a speed of 1 m/s and an altitude ranging from 1 to 4 meters above the ground level. In general, detecting and avoiding frontal obstacle is a quite challenging problem because optical flow has some limitation which should be taken into account i.e. lighting conditions and aperture problem.
Liste complète des métadonnées

https://hal-univ-bourgogne.archives-ouvertes.fr/hal-01488210
Contributeur : Le2i - Université de Bourgogne <>
Soumis le : lundi 13 mars 2017 - 14:30:35
Dernière modification le : jeudi 5 mars 2020 - 18:56:52

Identifiants

Collections

Citation

Mohamed Elawady, Ibrahim Sadek, Hiliwi Leake Kidane. Detecting and avoiding frontal obstacles from monocular camera for micro unmanned aerial vehicles. 2016, ⟨10.13140/RG.2.1.4769.4485⟩. ⟨hal-01488210⟩

Partager

Métriques

Consultations de la notice

233