Séminaire de Nguyen Dinh Van, doctorant en co-encadrement entre l'équipe RITS/INRIA Paris et l'Institut MICA - Date : jeudi 1er décembre 2016, 14h00 - Lieu : salle séminaire, Institut MICA, Hanoi University of Science and Technology


Intervenant :
M. Nguyen Dinh Van, doctorant co-encadré par l'équipe RITS/INRIA Paris et le département PSI de l'Institut MICA


Date : Jeudi 1er décembre 2016, 14h00
Lieu : salle "seminar room", 9ème étage, bâtiment B1, Institut MICA, Hanoi University of Science and Technology
Langue : le séminaire sera présenté en anglais


Recently, the problem of fully autonomous navigation of vehicle has gained major interest from research institutes and private companies. In general, these researches rely on GPS in fusion with other sensors to track vehicle in outdoor environment. However, as indoor environment such as car park is also an important scenario for vehicle navigation, the lack of GPS poses a serious problem. This study presents an approach to use WiFi Fingerprinting as a replacement for GPS information in order to allow seamlessly transition of localization architecture from outdoor to indoor environment. Often, movement speed of vehicle in indoor environment is low (10-12km/h) in comparison to outdoor scene but still surpasses human walking speed (3-5km/h, which is usually maximum movement speed for effective WiFi localization). This paper proposes an ensemble classification method together with a motion model in order to deal with the above issue. Experiments show that proposed method is capable of imitating GPS behavior on vehicle tracking.