IEEE International Conference on Intelligent Robots and Systems

Lucas De Paula Veronese, Edilson De Aguiar, Rafael Correia Nascimento, Jose Guivant, Fernando A.Auat Cheein, Alberto Ferreira De Souza, Thiago Oliveira-Santos

Research output: Contribution to conferencePaper

11 Citations (Scopus)


© 2015 IEEE. Vehicle localization in large-scale urban environments has been commonly addressed as a map-matching problem in the literature. Generally, the maps are 2D images of the world where each pixel covers a part of it. However, building maps for large-scale urban environments requires driving the vehicle along the desired path at least once. In order to simplify this task, in this work, we propose a new localization system that uses satellite aerial map-images available on the Internet to localize a vehicle in a complex urban environment. Satellite aerial map-images are compared against re-emission maps built from the infrared reflectance information of the vehicle's LiDAR. Normalized Mutual Information (NMI) is used to compare re-emission and aerial map images. A Particle Filter Localization strategy is applied for vehicle's localization. As a result, the system has an accuracy of 0.89m in a test course with 6.5km. Our system can be used continuously without losing track, and it works even in dark and partially occluded areas.
Original languageEnglish
Number of pages6
Publication statusPublished - 11 Dec 2015
Eventconference -
Duration: 11 Dec 2015 → …


Period11/12/15 → …

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    Veronese, L. D. P., De Aguiar, E., Nascimento, R. C., Guivant, J., Cheein, F. A. A., De Souza, A. F., & Oliveira-Santos, T. (2015). IEEE International Conference on Intelligent Robots and Systems. 4285-4290. Paper presented at conference, .