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IV 2013, IEEE Intelligent Vehicles Symposium 23/06/2013 26/06/2013 Gold Coast City Australie Proceedings IEEE
nom du congrès :
IV 2013, IEEE Intelligent Vehicles Symposium
début du congrès :
23/06/2013
fin du congrès :
26/06/2013
ville du congrès :
Gold Coast City
pays du congrès :
Australie
site des actes du congrès :
|
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Affiner la recherche Interroger des sources externesGeneration of an integrated 3D city model with visual landmarks for autonomous navigation in dense urban areas / Bahman Soheilian (June 2013)
Titre : Generation of an integrated 3D city model with visual landmarks for autonomous navigation in dense urban areas Type de document : Article/Communication Auteurs : Bahman Soheilian Editeur : New York : Institute of Electrical and Electronics Engineers IEEE Année de publication : June 2013 Projets : CityVIP / Paparoditis, Nicolas Conférence : IV 2013, IEEE Intelligent Vehicles Symposium 23/06/2013 26/06/2013 Gold Coast City Australie Proceedings IEEE Importance : pp 304 - 309 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Bases de données localisées
[Termes IGN] base de données localisées
[Termes IGN] bati
[Termes IGN] données localisées 3D
[Termes IGN] navigation autonome
[Termes IGN] route
[Termes IGN] vision par ordinateurRésumé : (auteur) In the context of urban autonomous navigation systems for going from point A to point B, a practicable trajectory which takes into account drivable areas and permanent obstacles should be designed first. A robot should then follow this trajectory while avoiding not only dynamic obstacles such as cars and pedestrians but also permanent obstacles such as road sides and central islands. To this end, a robot must be aware of its exact position and must be informed of what its immediate environment is at all times. In dense urban areas, GNSS systems generally suffer from lack of precision due to masks and multipaths. Localization systems have to model these phenomena and even merge with vision based methods in order to obtain the high accuracies required in the process. In this paper, we propose an integrated geographic database enabling, on the one hand, the GNSS and vision based localization methods to obtain the required accuracy, and on the other, to provide the robots with information about its surroundings such as drivable surfaces and permanent obstacles. The database is comprised of 3D buildings, 3D roads and a set of 3D visual landmarks. Our system provides most of the information required for autonomous navigation in dense urban areas and has successfully been embedded in real experiments, thanks to a real-time querying system. Numéro de notice : C2013-041 Affiliation des auteurs : LASTIG MATIS+Ext (2012-2019) Autre URL associée : vers HAL Thématique : INFORMATIQUE/POSITIONNEMENT Nature : Communication nature-HAL : ComAvecCL&ActesPubliésIntl DOI : 10.1109/IVS.2013.6629486 Date de publication en ligne : 15/10/2013 En ligne : https://doi.org/10.1109/IVS.2013.6629486 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=80148 Documents numériques
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Titre : Road side detection and reconstruction using Lidar sensor Type de document : Article/Communication Auteurs : Alexandre Hervieu Editeur : New York : Institute of Electrical and Electronics Engineers IEEE Année de publication : June 2013 Projets : 2-Pas d'info accessible - article non ouvert / Paparoditis, Nicolas Conférence : IV 2013, IEEE Intelligent Vehicles Symposium 23/06/2013 26/06/2013 Gold Coast City Australie Proceedings IEEE Importance : pp 1247 - 1252 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie
[Termes IGN] détection de contours
[Termes IGN] données lidar
[Termes IGN] données localisées 3D
[Termes IGN] filtre de Kalman
[Termes IGN] reconstruction 3D
[Termes IGN] route
[Termes IGN] trottoirRésumé : (auteur) Road edge localization is key knowledge for automatic road modeling and hence, in the field of autonomous vehicles. In this paper, we investigate the case of road border detection using LIDAR data. The aim is to propose a system recognizing curbs and curb ramps and to reconstruct the missing information in case of occlusion. A prediction/estimation process (inspired by Kalman filter models) has been analyzed. The map of angle deviation to ground normal is considered as a feature set, helping to characterize efficiently curbs while curb ramps and occluded curbs have been handled with the proposed model. Such a method may be used for both road map modeling and driver-assistance systems. A user interface scheme has also been described, providing an effective tool for semi-automatic processing of a large amount of data. Numéro de notice : C2013-042 Affiliation des auteurs : LASTIG MATIS (2012-2019) Thématique : IMAGERIE/INFORMATIQUE Nature : Communication nature-HAL : ComAvecCL&ActesPubliésIntl DOI : 10.1109/IVS.2013.6629637 Date de publication en ligne : 15/10/2013 En ligne : http://dx.doi.org/10.1109/IVS.2013.6629637 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=80223 Documents numériques
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Road side detection (poster)Adobe Acrobat PDF
