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Lidar-Inertial SLAM Method for Accurate and Robust Mapping

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Cognitive Systems and Information Processing (ICCSIP 2023)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 1918))

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Abstract

In recent studies on LiDAR SLAM, the achievement of robust optimized LiDAR odometry is the primary objective. For the mapping part, some studies focus on improving the processing of point cloud, while others aim to the optimization of the result deviation caused by errors. Meanwhile, in the fields of robotics and autonomous driving, multi-sensor fusion solutions based on IMUs are becoming the norm. This paper contributes to the optimization of mapping by leveraging a lightweight LiDAR-inertial state estimator. The proposed method combines information from a 6-axis IMU and a 3D LiDAR to form a tightly-coupled scheme that incorporates iterative error state Kalman filter (IESKF). Due to the continuous error accumulation, trajectory deviations can be significant. To mitigate this, an adaptive distance threshold loop closure detection mechanism is employed. Furthermore, since the algorithm primarily addresses outdoor scenes, ground features collected by sensors account for a significant portion of the computation. Improvements in the ground segmentation method lead to less disturbance during mapping on uneven terrain, enabling the method to effectively ad-dress a wider range of real-world environments. As a result, the proposed method demonstrates excellent stability and accuracy, as verified in experiments conducted on urban dataset and campus environment.

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Authors and Affiliations

  1. School of Mechanical Engineering and Automation, Fuzhou University, Fuzhou, 350116, China

    Yuhang Wang & Liwei Zhang

Authors
  1. Yuhang Wang
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  2. Liwei Zhang
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Correspondence to Liwei Zhang .

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Editors and Affiliations

  1. Tsinghua University, Beijing, China

    Fuchun Sun

  2. Southern University of Science and Technology, Shenzhen, China

    Qinghu Meng

  3. Henan University of Science and Technology, Luoyang, China

    Zhumu Fu

  4. Tsinghua University, Beijing, China

    Bin Fang

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© 2024 The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

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Wang, Y., Zhang, L. (2024). Lidar-Inertial SLAM Method for Accurate and Robust Mapping. In: Sun, F., Meng, Q., Fu, Z., Fang, B. (eds) Cognitive Systems and Information Processing. ICCSIP 2023. Communications in Computer and Information Science, vol 1918. Springer, Singapore. https://doi.org/10.1007/978-981-99-8018-5_3

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  • DOI: https://doi.org/10.1007/978-981-99-8018-5_3

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-99-8017-8

  • Online ISBN: 978-981-99-8018-5

  • eBook Packages: Computer ScienceComputer Science (R0)

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