Autonomous guidance for a uas along a staircase

Olivier De Meyst, Thijs Goethals, Haris Balta, Geert De Cubber, Rob Haelterman

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Résumé

In the quest for fully autonomous unmanned aerial systems (UAS), multiple challenges are faced. For enabling autonomous UAS navigation in indoor environments, one of the major bottlenecks is the capability to autonomously traverse narrow 3D - passages, like staircases. This paper presents a novel integrated system that implements a semiautonomous navigation system for a quadcopter. The navigation system permits the UAS to detect a staircase using only the images provided by an on-board monocular camera. A 3D model of this staircase is then automatically reconstructed and this model is used to guide the UAS to the top of the detected staircase. For validating the methodology, a proof of concept is created, based on the Parrot AR.Drone 2.0 which is a cheap commercial off-the-shelf quadcopter.

langue originaleAnglais
titreAdvances in Visual Computing - 11th International Symposium, ISVC 2015, Proceedings
rédacteurs en chefMark Elendt, Richard Boyle, Eric Ragan, Bahram Parvin, Rogerio Feris, Tim McGraw, Ioannis Pavlidis, Regis Kopper, George Bebis, Darko Koracin, Zhao Ye, Gunther Weber
EditeurSpringer
Pages466-475
Nombre de pages10
ISBN (imprimé)9783319278568
Les DOIs
étatPublié - 2015
Evénement11th International Symposium on Advances in Visual Computing, ISVC 2015 - Las Vegas, États-Unis
Durée: 14 déc. 201516 déc. 2015

Série de publications

NomLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume9474
ISSN (imprimé)0302-9743
ISSN (Electronique)1611-3349

Une conférence

Une conférence11th International Symposium on Advances in Visual Computing, ISVC 2015
Pays/TerritoireÉtats-Unis
La villeLas Vegas
période14/12/1516/12/15

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