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 |
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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 | |
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 |
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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