@inproceedings{b72f1629ba5c4ffeb83639b78a5a0476,
title = "Where Am I: Localization and 3d maps for autonomous vehicles",
abstract = "The nuts and bolts of autonomous driving find its root in devising the localization strategy. Lidar as one of the newest technologies developed in the recent years, provides rich information about the environment in the form of point cloud data which can be used for localization. In this paper, we discuss a localization approach which generates a 3D map from Lidar's point cloud data using Normal Distribution Transform (NDT) mapping. We use our own dataset collected using our self driving car KIA Soul EV equipped with Lidar and cameras. Once the 3D map has been generated, we have used NDT matching for localizing the self driving car.",
keywords = "3D Point Cloud, Autonomous Vehicles, Localization, Maps, NDT Matching",
author = "Farzeen Munir and Shoaib Azam and \{Muqeem Sheri\}, Ahmad and Ko, \{Yeong Min\} and Moongu Jeon",
note = "Publisher Copyright: {\textcopyright} 2019 by SCITEPRESS - Science and Technology Publications, Lda.; 5th International Conference on Vehicle Technology and Intelligent Transport Systems, VEHITS 2019 ; Conference date: 03-05-2019 Through 05-05-2019",
year = "2019",
doi = "10.5220/0007718404520457",
language = "English",
series = "VEHITS 2019 - Proceedings of the 5th International Conference on Vehicle Technology and Intelligent Transport Systems",
publisher = "SciTePress",
pages = "452--457",
editor = "Oleg Gusikhin and Markus Helfert",
booktitle = "VEHITS 2019 - Proceedings of the 5th International Conference on Vehicle Technology and Intelligent Transport Systems",
}