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Intelligent Service Robotics
Published in: Intelligent Service Robotics 2/2022

25-11-2021 | Original Research Paper

What if there was no revisit? Large-scale graph-based SLAM with traffic sign detection in an HD map using LiDAR inertial odometry

Authors: Changki Sung, Seulgi Jeon, Hyungtae Lim, Hyun Myung

Published in: Intelligent Service Robotics | Issue 2/2022

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Abstract

Accurate localization and mapping in a large-scale environment is an essential system of an autonomous vehicle. The difficulty of the previous LiDAR or LiDAR-inertial simultaneous localization and mapping (SLAM) methods is correcting long-term drift error in a large-scale environment. This paper proposes a novel approach of a large-scale, graph-based SLAM with traffic sign data involved in a high-definition (HD) map. The graph of the system is structured with the inertial measurement unit (IMU) factor, LiDAR-inertial odometry factor, map-matching factor, and loop closure factor. The local sliding window-based optimization method is employed for real-time processing. As a result, the proposed method improves the accuracy of the localization and mapping compared with the state-of-the-art LiDAR or LiDAR-inertial SLAM methods. In addition, the proposed method can localize accurately without revisit, required for conventional graph-based SLAM for graph optimization, unlike previous studies. The proposed method is intensively validated with a data set collected in a city where the Global Navigation Satellite System (GNSS) signal is unreliable and on a university campus.
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Metadata
Title
What if there was no revisit? Large-scale graph-based SLAM with traffic sign detection in an HD map using LiDAR inertial odometry
Authors
Changki Sung
Seulgi Jeon
Hyungtae Lim
Hyun Myung
Publication date
25-11-2021
Publisher
Springer Berlin Heidelberg
Published in
Intelligent Service Robotics / Issue 2/2022
Print ISSN: 1861-2776
Electronic ISSN: 1861-2784
DOI
https://doi.org/10.1007/s11370-021-00395-2

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