Laser & Optoelectronics Progress, Volume. 60, Issue 14, 1428006(2023)

SLAM Algorithm with Tight Coupling of Vision and LiDAR Odometer

Wenhan Liu, Lingyu Sun, Qingxiang Li*, Xiaoyu Du, Wei Wang, and Hongliang Qin
Author Affiliations
  • School of Machanical Engineerings, Hebei University of Technology, Tianjin 300000, China
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    Figures & Tables(15)
    Coordinate system conversion
    System integration block diagram
    Comparison of different detectors. (a) (c) Proposed characteristic detector; (b) (d) feature detector based on Shi Tomasi and BRISK
    Lidar odometer point cloud scan. (a) Lidar odometer scan front view; (b) lidar odometer scan top view
    Scan context descriptor
    KITTI 05 and KITTI 00 global and local point cloud maps. (a) KITTI 05 global point cloud map; (b) KITTI 05 local point cloud map; (c) KITTI 00 global point cloud map; (d) KITTI 00 local point cloud map
    Factor diagram structure
    Odometer gravity vector drift comparison of proposed algorithm and V-LOAM. (a)(b)(c) Localization effect of proposed algorithm when vector drift occurs in V-LOAM; (d)(e)(f) gravity vector drift phenomenon that occurs in V-LOAM
    Odometer positional drift comparison of proposed algorithm and V-LOAM. (a)(b) Positioning effect of proposed algorithm when V-LOAM has positional drift; (c) (d) positional drift phenomenon in V-LOAM
    Local map accuracy comparison of proposed algorithm and V-LOAM. (a) Local map effect of proposed algorithm; (b) V-LOAM local map loopback failure
    Comparison of proposed algorithm, LeGO-LOAM, V-LOAM in KITTI 05, 06, 09 with true value trajectory. (a) KITTI 05 track comparison; (b) KITTI 06 track comparison; (c) KITTI 09 track comparison; (d) KITTI 05 track details; (e) KITTI 06 track details; (f) KITTI 09 track details;
    Comparison of proposed algorithm, LeGO-LOAM, V-LOAM in KITTI 00 with true value trajectory. (a) KITTI 00 track comparison; (b) KITTI 00 track details
    • Table 1. Feature point detector combination

      View table

      Table 1. Feature point detector combination

      Detector typeDescriptor typeMatcher typeSelect type
      SIFTORBBFKNN
    • Table 2. Comparison of SV-LOAM, V-LOAM, LeGO-LOAM absolute trajectory error (APE) and relative position error (RPE)

      View table

      Table 2. Comparison of SV-LOAM, V-LOAM, LeGO-LOAM absolute trajectory error (APE) and relative position error (RPE)

      AlgorithmEvaluation errorKITTI 05KITTI 06KITTI 09
      Max /mMin /mMean /mMax /mMin /mMean /mMax /mMin /mMean /m
      SV-LOAMAPE3.80.22.62.92.42.73.00.31.6
      RPE5.61.32.50.60.10.33.21.92.6
      V-LOAMAPE360.435.6108.7423.944.6142.6390.213.5109.0
      RPE1872.428.0192.84.329.0152.03.026.3
      LeGO-LOAMAPE9.40.33.45.20.32.967.11.711.6
      RPE5.21.62.65.41.02.05.01.02.8
    • Table 3. Comparison of SV-LOAM, V-LOAM, and LeGO-LOAM errors in KITTI 00 dataset

      View table

      Table 3. Comparison of SV-LOAM, V-LOAM, and LeGO-LOAM errors in KITTI 00 dataset

      AlgorithmEvaluation errorKITTI 00
      Max /mMin /mMean /mRMSE /mStd /m
      SV-LOAMAPE4.32.42.93.00.4
      RPE5.60.41.71.80.9
      V-LOAMAPE402.1170.428.0190.284.4
      RPE153.13.228.737.924.7
      LeGO-LOAMAPE13.63.45.25.82.4
      RPE5.40.62.01.91.1
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    Wenhan Liu, Lingyu Sun, Qingxiang Li, Xiaoyu Du, Wei Wang, Hongliang Qin. SLAM Algorithm with Tight Coupling of Vision and LiDAR Odometer[J]. Laser & Optoelectronics Progress, 2023, 60(14): 1428006

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    Paper Information

    Category: Remote Sensing and Sensors

    Received: Jun. 6, 2022

    Accepted: Aug. 12, 2022

    Published Online: Jul. 17, 2023

    The Author Email: Qingxiang Li (734579675@qq.com)

    DOI:10.3788/LOP221767

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