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Improving trajectory estimation using 3D city models and kinematic point clouds / Lucas Lucks in Transactions in GIS, Vol 25 n° 1 (February 2021)  

Public [article]  inTransactions in GIS > Vol 25 n° 1 (February 2021) . - pp 238 - 260 Titre : Improving trajectory estimation using 3D city models and kinematic point clouds Type de document : Article/Communication Auteurs : Lucas Lucks, Auteur ; Lasse Klingbeil, Auteur ; Lutz Plümer, Auteur ; Youness Dehbi, Auteur Année de publication : 2021 Article en page(s) : pp 238 - 260 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Navigation et positionnement [Termes IGN] algorithme ICP [Termes IGN] bruit (théorie du signal) [Termes IGN] centrale inertielle [Termes IGN] classification par forêts d'arbres décisionnels [Termes IGN] données lidar [Termes IGN] données localisées 3D [Termes IGN] interpolation [Termes IGN] milieu urbain [Termes IGN] modèle 3D de l'espace urbain [Termes IGN] modèle sémantique de données [Termes IGN] navigation autonome [Termes IGN] semis de points Résumé : (Auteur) Accurate and robust positioning of vehicles in urban environments is of high importance for autonomous driving or mobile mapping. In mobile mapping systems, a simultaneous mapping of the environment using laser scanning and an accurate positioning using global navigation satellite systems are targeted. This requirement is often not guaranteed in shadowed cities where global navigation satellite system signals are usually disturbed, weak or even unavailable. We propose a novel approach which incorporates prior knowledge (i.e., a 3D city model of the environment) and improves the trajectory. The recorded point cloud is matched with the semantic city model using a point‐to‐plane iterative closest point method. A pre‐classification step enables an informed sampling of appropriate matching points. Random forest is used as classifier to discriminate between facade and remaining points. Local inconsistencies are tackled by a segmentwise partitioning of the point cloud where an interpolation guarantees a seamless transition between the segments. The general applicability of the method implemented is demonstrated on an inner‐city data set recorded with a mobile mapping system. Numéro de notice : A2021-188 Affiliation des auteurs : non IGN Thématique : IMAGERIE/POSITIONNEMENT Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1111/tgis.12719 Date de publication en ligne : 02/01/2021 En ligne : https://doi.org/10.1111/tgis.12719 Format de la ressource électronique : URL Article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=97157 [article]