Improving Poor GPS Area Localization for Intelligent Vehicles - Inria - Institut national de recherche en sciences et technologies du numérique Access content directly
Conference Papers Year : 2017

Improving Poor GPS Area Localization for Intelligent Vehicles


Precise positioning plays a key role in successful navigation of autonomous vehicles. A fusion architecture of Global Positioning System (GPS) and Laser-SLAM (Simultaneous Localization and Mapping) is widely adopted. While Laser-SLAM is known for its highly accurate localization, GPS is still required to overcome accumulated error and give SLAM a required reference coordinate. However, there are multiple cases where GPS signal quality is too low or not available such as in multi-story parking, tunnel or urban area due to multipath propagation issue etc. This paper proposes an alternative approach for these areas with WiFi Fingerprinting technique to replace GPS. Result obtained from WiFi Fingerprinting will then be fused with Laser-SLAM to maintain the general architecture, allow seamless adaptation of vehicle to the environment.
Fichier principal
Vignette du fichier
finalVersion.pdf (1.17 Mo) Télécharger le fichier
Origin : Files produced by the author(s)

Dates and versions

hal-01613132 , version 1 (09-10-2017)


  • HAL Id : hal-01613132 , version 1


Dinh-Van Ngdvan Nguyen, Fawzi Nashashibi, Trung-Kien Dao, Eric Castelli. Improving Poor GPS Area Localization for Intelligent Vehicles. MFI 2017 - IEEE International Conference on Multisensor Fusion and Integration for Intelligent Systems, Nov 2017, Daegu, South Korea. pp.1-5. ⟨hal-01613132⟩
208 View
523 Download


Gmail Facebook X LinkedIn More