@inproceedings{7a264193a5f747aa9a1bcae31e3eb967,
title = "Multi-LiDAR Localization and Mapping Pipeline for Urban Autonomous Driving",
abstract = "Autonomous vehicles require accurate and robust localization and mapping algorithms to navigate safely and reliably in urban environments. We present a novel sensor fusion-based pipeline for offline mapping and online localization based on LiDAR sensors. The proposed approach leverages four LiDAR sensors. Mapping and localization algorithms are based on the KISS-ICP, enabling real-time performance and high accuracy. We introduce an approach to generate semantic maps for driving tasks such as path planning. The presented pipeline is integrated into the ROS 2 based Autoware software stack, providing a robust and flexible environment for autonomous driving applications. We show that our pipeline outperforms state-of-the-art approaches for a given research vehicle and real-world autonomous driving application.",
keywords = "Autonomous Vehicles, LiDAR, Maps, SLAM, Sensor Fusion",
author = "Florian Sauerbeck and Dominik Kulmer and Markus Pielmeier and Maximilian Leitenstern and Christoph Weiss and Johannes Betz",
note = "Publisher Copyright: {\textcopyright} 2023 IEEE.; 2023 IEEE SENSORS, SENSORS 2023 ; Conference date: 29-10-2023 Through 01-11-2023",
year = "2023",
doi = "10.1109/SENSORS56945.2023.10325207",
language = "English",
series = "Proceedings of IEEE Sensors",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
booktitle = "2023 IEEE SENSORS, SENSORS 2023 - Conference Proceedings",
}