• Laser & Optoelectronics Progress
  • Vol. 58, Issue 3, 3280041 (2021)
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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    DOI: 10.3788/LOP202158.0328004 Cite this Article Set citation alerts
    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 Copy Citation Text show less
    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
    LiDAR installation schematic. (a) Front view; (b) side view
    Fig. 2. LiDAR installation schematic. (a) Front view; (b) side view
    Vehicle and LiDAR coordinate systems
    Fig. 3. Vehicle and LiDAR coordinate systems
    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
    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
    Particle group algorithm flow diagram
    Fig. 6. Particle group algorithm flow diagram
    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
    Tunnel cross-section point cloud
    Fig. 8. Tunnel cross-section point cloud
    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)
    LiDAR installation diagram. (a) Front view; (b) side view
    Fig. 10. LiDAR installation diagram. (a) Front view; (b) side view
    Point cloud of cross section of tunnel
    Fig. 11. Point cloud of cross section of tunnel
    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
    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 1. Comparison of detection deviation and actual value of each algorithm
    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
    Table 2. Difference between measured tunnel center and design center
    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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