Visual localization and servoing for drone use in indoor remote laboratory environment - CNRS - Centre national de la recherche scientifique Accéder directement au contenu
Article Dans Une Revue Machine Vision and Applications Année : 2021

Visual localization and servoing for drone use in indoor remote laboratory environment

Résumé

In this paper, we present a localization system for the use of drone in a remote lab. The objective is to allow a drone to inspect remote electronic instruments autonomously, as well as to return to its base and land on a platform for the recharge of its batteries. In addition, the drone should be able to detect the presence of a teacher in the lab, and to center the human face in the image in order to enable remote student-teacher communication. To achieve the first objective, the localization approach is composed of a monocular SLAM (Simultaneous Localization and Mapping) algorithm PTAM (Parallel Tracking and Mapping) and an estimation based on the homography transform. For the face-drone servoing, the approach is based on the 3D Candide model. Both approaches work in real-time. Quantitative and qualitative experiments are presented that show the robustness of both methods.
Fichier principal
Vignette du fichier
journal_paper_Machine_Vision_And_Applications.pdf (1.48 Mo) Télécharger le fichier
Origine : Fichiers produits par l'(les) auteur(s)

Dates et versions

hal-03126470 , version 1 (31-01-2021)

Identifiants

Citer

Fawzi Khattar, Franck Luthon, Benoît Larroque, Fadi Dornaika. Visual localization and servoing for drone use in indoor remote laboratory environment. Machine Vision and Applications, 2021, 32 (1), pp.32. ⟨10.1007/s00138-020-01161-7⟩. ⟨hal-03126470⟩
140 Consultations
187 Téléchargements

Altmetric

Partager

Gmail Facebook X LinkedIn More