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Laser & Optoelectronics Progress, Volume. 58, Issue 3, 3280041(2021)

LiDAR Real-Time Detection of Tunnel Centerline Based on Particle Swarm Optimization Algorithm

Wang Yanglang1, Wang Kewei1,2, and Zou Bin1,2、*
Author Affiliations
  • 1Hubei Key Laboratory of Advanced Technology for Automotive Components, Wuhan University of Technology, Wuhan , Hubei 430070, China
  • 2Hubei Collaborative Innovation Center for Automotive Components Technology, Wuhan University of Technology, Wuhan , Hubei 430070, China
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    AbstractGet PDF(in Chinese)
    Figures&Tables (14)
    Equations (2)
    References (17)
    Cited By (3)
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    Figures & Tables(14)
    Basic parameters and basic principles of LiDAR. (a) Schematic diagram of laser emission; (b)basic parameters

    Fig. 1. Basic parameters and basic principles of LiDAR. (a) Schematic diagram of laser emission; (b)basic parameters

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    LiDAR installation schematic. (a) Front view; (b) side view

    Fig. 2. LiDAR installation schematic. (a) Front view; (b) side view

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    Vehicle and LiDAR coordinate systems

    Fig. 3. Vehicle and LiDAR coordinate systems

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    Cloud diagram of the vehicle turning to the right to the tunnel point

    Fig. 4. Cloud diagram of the vehicle turning to the right to the tunnel point

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    Point cloud in the longitudinal reference direction of the tunnel. (a) Two-dimensional schematic diagram of point cloud; (b) three-dimensional schematic diagram of point cloud; (c) LiDAR point cloud with vertical field angle of 1°; (d) point cloud in the longitudinal reference direction of the tunnel

    Fig. 5. Point cloud in the longitudinal reference direction of the tunnel. (a) Two-dimensional schematic diagram of point cloud; (b) three-dimensional schematic diagram of point cloud; (c) LiDAR point cloud with vertical field angle of 1°; (d) point cloud in the longitudinal reference direction of the tunnel

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    Particle group algorithm flow diagram

    Fig. 6. Particle group algorithm flow diagram

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    Top view of point cloud coordinate conversion of tunnel wall. (a) Original point cloud; (b) post-conversion point cloud; (c) comparison chart

    Fig. 7. Top view of point cloud coordinate conversion of tunnel wall. (a) Original point cloud; (b) post-conversion point cloud; (c) comparison chart

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    Tunnel cross-section point cloud

    Fig. 8. Tunnel cross-section point cloud

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    Fitting effect diagrams. (a) Particle swarm optimization algorithm; (b) least squares method (circle); (c) least squares method (ellipse)

    Fig. 9. Fitting effect diagrams. (a) Particle swarm optimization algorithm; (b) least squares method (circle); (c) least squares method (ellipse)

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    LiDAR installation diagram. (a) Front view; (b) side view

    Fig. 10. LiDAR installation diagram. (a) Front view; (b) side view

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    Point cloud of cross section of tunnel

    Fig. 11. Point cloud of cross section of tunnel

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    Test results. (a) Original point cloud; (b) converted point cloud; (c) center point of tunnel cross section; (d) fitting result of tunnel centerline

    Fig. 12. Test results. (a) Original point cloud; (b) converted point cloud; (c) center point of tunnel cross section; (d) fitting result of tunnel centerline

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    • Table 1. Comparison of detection deviation and actual value of each algorithm

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      Table 1. Comparison of detection deviation and actual value of each algorithm

      Real valueFitting value

      PSO algorithm

      （ t = 87 ms·frame-1;f= 12.3 Hz）

      		Least-square method (circle；t= 112 ms·frame-1;f= 8.9 Hz）Least-square method (ellipse; t= 136 ms·frame-1; f= 7.4 Hz）
      Raduis /mΔy /mmRaduis /mΔy /mmRaduis /mΔy /mmEccentricityΔy /mm
      6.700-506.680-366.679-350.163-31
      6.7001006.6731066.6721060.15987
      6.7001506.6711366.6711370.170101

    • Table 2. Difference between measured tunnel center and design center

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      Table 2. Difference between measured tunnel center and design center

      Section numberMeasured tunnel section dataDifference of center /mmMean difference /mm
      Position of the two sectionsSection radius /m
      1X=0.1 m,X=0.2 m6.67989698
      6.6868587
      6.6758649
      2X=0.2 m,X=0.3 m6.6762851211
      6.67850211
      6.68352111
      3X=0.3 m,X=0.4 m6.6812541012
      6.67552913
      6.68014512
      4X=0.4 m,X=0.5 m6.670158911
      6.67787413
      6.67598712
      5X=5.6 m,X=5.8 m6.6801321515
      6.67789514
      6.67852917
      6X=6.4 m,X=6.7 m6.6715141920
      6.67910422
      6.66909819
      7X=7.4 m,X=7.7 m6.6820562426
      6.67002528
      6.67150625
      8X=8.4 m,X=8.7 m6.6690141823
      6.67028923
      6.66581426
      9X=9.4 m,X=9.7 m6.6785132629
      6.67148529
      6.67658231
      10X=10.4 m,X=10.7 m6.6626772930
      6.67090527
      6.66854933
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    Wang Yanglang, Wang Kewei, Zou Bin. LiDAR Real-Time Detection of Tunnel Centerline Based on Particle Swarm Optimization Algorithm[J]. Laser & Optoelectronics Progress, 2021, 58(3): 3280041

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    Paper Information

    Category: Remote Sensing and Sensors

    Received: Jun. 16, 2020

    Accepted: --

    Published Online: Mar. 12, 2021

    The Author Email: Bin Zou (1173059950@qq.com)

    DOI:10.3788/LOP202158.0328004

    Topics

    laser devices and laser physics
    Lasers and Laser Optics
    Laser physics
    laser manufacturing
    Instrumentation, Measurement and Metrology