inria-00332441, version 1

Multi-sensors data fusion using dynamic bayesian network for robotised vehicle geo-localisation

Cindy Cappelle () ^a, 1, Maan El Badaoui El Najjar () ^a, 1, Denis Pomorski () ^a, 1, François Charpillet () ^b, 2

11th International Conference on Information Fusion (2008) 1-8

• a –  Université des Sciences et Technologies de Lille - Lille I
• b –  LORIA
• 1:  Laboratoire d'Automatique, Génie Informatique et Signal (LAGIS)
• http://lagis.ec-lille.fr/
  CNRS : UMR8146 – Université Lille I - Sciences et technologies – Ecole Centrale de Lille LAGIS Ecole Centrale de Lille Cité Scientifique 59655 Villeneuve d'Ascq France
• 2:  MAIA (INRIA Lorraine - LORIA)
• 
  INRIA – CNRS : UMR7503 – Université Henri Poincaré - Nancy I – Université Nancy II – Institut National Polytechnique de Lorraine (INPL) France

Bibliographic reference

• Type of document: Peer-reviewed conferences/proceedings
• Domain:

  Computer Science/Robotics

  Computer Science/Automatic Control Engineering

• Title: Multi-sensors data fusion using dynamic bayesian network for robotised vehicle geo-localisation
• Abstract: This paper presents an outdoor geolocalisation 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 acquired 2D images and the virtual 3D city model. This estimation is especially useful during long GPS outages to correct the drift of the only dead-reckoning localisation or when the GPS quality is deteriorated due to multi-path, satellites masks and so on particularly in urban environments. Moreover, the various sensors measurements are fused in Dynamic Bayesian Network formalism in order to provide a continuous estimation of the pose.
• Full text language: English
• Publication date: 2008
• Audience: international
• Conference title: 11th International Conference on Information Fusion
• Conference city: Cologne
• Country: Germany
• Conference date: 2008-07-01
• Commercial editor: IEEE
• Pagination: 1-8
• Keywords: Geo-localisation – Virtual 3D City Model – 3D Geographical Information System (3D-GIS) – Global Positioning System (GPS) – Vision – Dynamic Bayesian Network (DBN) – 2D/3D Matching

• inria-00332441, version 1
• http://hal.inria.fr/inria-00332441
• oai:hal.inria.fr:inria-00332441
• From: Cindy Cappelle <>
• Submitted on: Tuesday, 21 October 2008 09:20:16
• Updated on: Tuesday, 6 March 2012 12:08:14