Cindy Cappelle

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Vehicle geo-localization in urban areas remains to be challenging problems. For this purpose, Global Positioning System (GPS) receiver is usually the main sensor. But, the use of GPS alone is not sufficient in many urban environments due to wave multi-path. In order to provide accurate and robust localization, GPS has so to be helped with other sensors like(More)
This paper presents an outdoor geo-localisation method, which integrates several information sources: measurements from GPS, incremental encoders and gyroscope, 2D images provided by an on-board camera and a virtual 3D city model. A 3D cartographical observation of the vehicle pose is constructed. This observation is based on the matching between the(More)
Current perception systems of intelligent vehicles not only make use of visual sensors, but also take advantage of depth sensors. Extrinsic calibration of these heterogeneous sensors is required for fusing information obtained separately by vision sensors and light detection and ranging (LIDARs). In this paper, an optimal extrinsic calibration algorithm(More)
This paper presents a novel extrinsic calibration algorithm between a binocular stereo vision system and a 2D LIDAR (laser range finder). Extrinsic calibration of these heterogeneous sensors is required to fuse information obtained separately by vision sensor and LIDAR in the context of intelligent vehicle. By placing a planar chessboard at different(More)
Vehicle localization and autonomous navigation consist of precisely positioning a vehicle on road by the use of different kinds of sensors. This paper presents a vehicle localization method by integrating a stereoscopic system, a laser range finder (LRF) and a global localization sensor GPS. For more accurate LRF-based vehicle motion estimation, an(More)
This paper proposed a new vehicle geo-localization method in urban environment integrating a new source of information that is a virtual 3D city model. This 3D model provides a realistic representation of the navigation environment of the vehicle. To optimize the performance of vehicle geo-localization system, several sources of information are integrated(More)
An Unscented Information Filter (UIF) based multi-sensor fusion method for ground vehicles localization in urban environments is presented and evaluated. UIF is used to fuse information acquired from a stereo vision system, a laser range finder and a GPS receiver in order to provide more robust vehicle localization results. Stereovision based visual(More)
Intelligent Geolocalization in Urban Areas Using Global Positioning Systems, Three-Dimensional Geographic Information Systems, and Vision Cindy Cappelle a , Maan El Badaoui El Najjar b , Denis Pomorski c & François Charpillet b a Laboratoire Systèmes et Transports , Université de Technologie de Belfort-Montbéliard , b Laboratoire Lorrain de Recherche en(More)
Visual sensors and depth sensors, such as camera and LIDAR (Light Detection and Ranging) are more and more used together in current perception systems of intelligent vehicles. Fusing information obtained separately from these heterogeneous sensors always requires extrinsic calibration of vision sensors and LIDARs. In this paper, we propose an optimal(More)