Virtual 3D city model for navigation in urban areas

Abstract : In this paper, we propose to study the integration of a new source of a priori information, which is the virtual 3D city model. We study this integration for two tasks: vehicles geolocalization and obstacles detection. A virtual 3D city model is a realistic representation of the evolution environment of a vehicle. It is a database of geographical and textured 3D data. We describe an ego-localization method that combines measurements of a GPS (Global Positioning System) receiver, odometers, a gyrometer, a video camera and a virtual 3D city model. GPS is often consider as the main sensor for localization of vehicles. But, in urban areas, GPS is not precise or even can be unavailable. So, GPS data are fused with odometers and gyrometer measurements using an Unscented Kalman Filter (UKF). However, during long GPS unavailability, localization with only odometers and gyrometer drift. Thus, we propose a new observation of the location of the vehicle. This observation is based on the matching between the current image acquired by an onboard camera and the virtual 3D city model of the environment. We also propose an obstacle detection method based on the comparison between the image acquired by the on-board camera and the image extracted from the 3D model. The following principle is used: the image acquired by the on-board camera contains the possible dynamic obstacles whereas they are absent from the 3D model. The two proposed concepts are tested on real data.
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Contributor : Denis Pomorski <>
Submitted on : Tuesday, April 18, 2017 - 11:06:35 AM
Last modification on : Saturday, March 30, 2019 - 1:26:32 AM

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Cindy Cappelle, Maan El Badaoui El Najjar, Denis Pomorski, François Charpillet. Virtual 3D city model for navigation in urban areas. Journal of Intelligent and Robotic Systems, Springer Verlag (Germany), 2012, 66 (3), pp.377-399. ⟨Springer⟩. ⟨10.1007/s10846-011-9594-0⟩. ⟨hal-01509574⟩



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