Re-emission and satellite aerial maps applied to vehicle localization on urban environments

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

doi:10.1109/IROS.2015.7353984

Re-emission and satellite aerial maps applied to vehicle localization on urban environments

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

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

33 Citations (Scopus)

Abstract

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 language	English
Title of host publication	2015 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)
Publisher	IEEE
Pages	4285-4290
Number of pages	6
ISBN (Electronic)	9781479999941
DOIs	https://doi.org/10.1109/IROS.2015.7353984
Publication status	Published - 17 Dec 2015
Event	28th IEEE/RSJ International Conference on Intelligent Robots and Systems 2015 - Hamburg, Germany Duration: 28 Sept 2015 → 2 Oct 2015

Conference

Conference	28th IEEE/RSJ International Conference on Intelligent Robots and Systems 2015
Abbreviated title	IROS 2015
Country/Territory	Germany
City	Hamburg
Period	28/09/15 → 2/10/15

ASJC Scopus subject areas

Control and Systems Engineering
Software
Computer Vision and Pattern Recognition
Computer Science Applications

Access to Document

10.1109/IROS.2015.7353984

Cite this

de Paula Veronese, L., De Aguiar, E., Correia Nascimento, R., Guivant, J., Auat Cheein, F. A., Ferreira de Souza, A., & Oliveira-Santos, T. (2015). Re-emission and satellite aerial maps applied to vehicle localization on urban environments. In 2015 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) (pp. 4285-4290). IEEE. https://doi.org/10.1109/IROS.2015.7353984

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title = "Re-emission and satellite aerial maps applied to vehicle localization on urban environments",

abstract = "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.",

author = "\{de Paula Veronese\}, Lucas and \{De Aguiar\}, Edilson and \{Correia Nascimento\}, Rafael and Jos{\'e} Guivant and \{Auat Cheein\}, \{Fernando A.\} and \{Ferreira de Souza\}, Alberto and Thiago Oliveira-Santos",

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de Paula Veronese, L, De Aguiar, E, Correia Nascimento, R, Guivant, J, Auat Cheein, FA, Ferreira de Souza, A & Oliveira-Santos, T 2015, Re-emission and satellite aerial maps applied to vehicle localization on urban environments. in 2015 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS). IEEE, pp. 4285-4290, 28th IEEE/RSJ International Conference on Intelligent Robots and Systems 2015, Hamburg, Germany, 28/09/15. https://doi.org/10.1109/IROS.2015.7353984

Re-emission and satellite aerial maps applied to vehicle localization on urban environments. / de Paula Veronese, Lucas; De Aguiar, Edilson; Correia Nascimento, Rafael et al.
2015 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS). IEEE, 2015. p. 4285-4290.

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

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AU - de Paula Veronese, Lucas

AU - De Aguiar, Edilson

AU - Correia Nascimento, Rafael

AU - Guivant, José

AU - Auat Cheein, Fernando A.

AU - Ferreira de Souza, Alberto

AU - Oliveira-Santos, Thiago

PY - 2015/12/17

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N2 - 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.

AB - 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.

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Re-emission and satellite aerial maps applied to vehicle localization on urban environments

Abstract

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ASJC Scopus subject areas

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