Intelligent geo-localisation in urban areas ...
Document type :
Compte-rendu et recension critique d'ouvrage
Title :
Intelligent geo-localisation in urban areas using global positioning systems, 3dimensional geographic information systems, and vision
Author(s) :
Cappelle, Cindy [Auteur]
Laboratoire Systèmes et Transports [SET]
Autonomous intelligent machine [MAIA]
El Badaoui El Najjar, Maan [Auteur]
Systèmes Tolérants aux Fautes [STF]
Autonomous intelligent machine [MAIA]
Pomorski, Denis [Auteur]
Systèmes Tolérants aux Fautes [STF]
Charpillet, François [Auteur]
Autonomous intelligent machine [MAIA]
Laboratoire Systèmes et Transports [SET]
Autonomous intelligent machine [MAIA]
El Badaoui El Najjar, Maan [Auteur]

Systèmes Tolérants aux Fautes [STF]
Autonomous intelligent machine [MAIA]
Pomorski, Denis [Auteur]

Systèmes Tolérants aux Fautes [STF]
Charpillet, François [Auteur]
Autonomous intelligent machine [MAIA]
Journal title :
Journal of Intelligent Transportation Systems: Technology, Planning, and Operations
Pages :
3 - 12
Publisher :
Taylor & Francis: STM, Behavioural Science and Public Health Titles
Publication date :
2010
ISSN :
1547-2450
HAL domain(s) :
Informatique [cs]/Robotique [cs.RO]
English abstract : [en]
This article tackles the problem of a vehicle's geolocalization in urban areas. For this purpose, Global Positioning System (GPS) receiver is the main sensor. However, the use of GPS alone is not sufficient in many urban ...
Show more >This article tackles the problem of a vehicle's geolocalization in urban areas. For this purpose, Global Positioning System (GPS) receiver is the main sensor. However, the use of GPS alone is not sufficient in many urban environments. GPS has to be helped with dead-reckoned sensors, map data, and cameras. A novel observation of the absolute pose of the vehicle is proposed to back up GPS and the drift of dead-reckoned sensors. This approach uses a new source of information that is a geographical 3-dimensional (3D) model of the environment in which the vehicle navigates. This virtual 3D city model is managed in real time by a 3D geographical information system (3D GIS). This pose's observation is constructed by matching the virtual image provided by the 3D GIS and the real image acquired by an onboard camera. An extended Kalman filter combines the sensors measurements to produce an estimation of the vehicle's pose. Experimental results using data from an odometer, a gyroscope, a GPS receiver, a camera, and an accurate geographical 3D model of the environment illustrate the developed approach.Show less >
Show more >This article tackles the problem of a vehicle's geolocalization in urban areas. For this purpose, Global Positioning System (GPS) receiver is the main sensor. However, the use of GPS alone is not sufficient in many urban environments. GPS has to be helped with dead-reckoned sensors, map data, and cameras. A novel observation of the absolute pose of the vehicle is proposed to back up GPS and the drift of dead-reckoned sensors. This approach uses a new source of information that is a geographical 3-dimensional (3D) model of the environment in which the vehicle navigates. This virtual 3D city model is managed in real time by a 3D geographical information system (3D GIS). This pose's observation is constructed by matching the virtual image provided by the 3D GIS and the real image acquired by an onboard camera. An extended Kalman filter combines the sensors measurements to produce an estimation of the vehicle's pose. Experimental results using data from an odometer, a gyroscope, a GPS receiver, a camera, and an accurate geographical 3D model of the environment illustrate the developed approach.Show less >
Language :
Anglais
Popular science :
Non
Collections :
Source :