• Chinese Journal of Lasers
  • Vol. 48, Issue 24, 2410001 (2021)
Jie Hu1、2、3、*, Han Liu1、2、3, Wencai Xu1、2、3, and Liang Zhao1、2、3
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
  • 3Hubei Research Center for New Energy & Intelligent Connected Vehicle, Wuhan University of Technology, Wuhan, Hubei 430070, China;
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    DOI: 10.3788/CJL202148.2410001 Cite this Article Set citation alerts
    Jie Hu, Han Liu, Wencai Xu, Liang Zhao. Position Detection Algorithm of Road Obstacles Based on 3D LiDAR[J]. Chinese Journal of Lasers, 2021, 48(24): 2410001 Copy Citation Text show less
    Flow chart of objection position detection algorithm
    Fig. 1. Flow chart of objection position detection algorithm
    Sector bins distribution and polar coordinate system
    Fig. 2. Sector bins distribution and polar coordinate system
    Pseudo-code block diagram of ground segmentation algorithm
    Fig. 3. Pseudo-code block diagram of ground segmentation algorithm
    Schematic diagram of point cloud projected by LiDAR
    Fig. 4. Schematic diagram of point cloud projected by LiDAR
    Comparison of point clouds from different perspectives. (a) 3D view; (b) XOY plane view
    Fig. 5. Comparison of point clouds from different perspectives. (a) 3D view; (b) XOY plane view
    Object direction angle detection
    Fig. 6. Object direction angle detection
    Coordinate system rotation process
    Fig. 7. Coordinate system rotation process
    Pseudo code block diagram of direction and size detection algorithm
    Fig. 8. Pseudo code block diagram of direction and size detection algorithm
    Installation drawing of vehicle sensor
    Fig. 9. Installation drawing of vehicle sensor
    Detection performance of the algorithm. (a) Velodyne VLP16; (b) LEISHEN C32151L; (c) ZVISION ML-30S
    Fig. 10. Detection performance of the algorithm. (a) Velodyne VLP16; (b) LEISHEN C32151L; (c) ZVISION ML-30S
    Detection time of different LiDARs. (a) Velodyne VLP16; (b) LEISHEN C32151L; (c) ZVISION ML-30S
    Fig. 11. Detection time of different LiDARs. (a) Velodyne VLP16; (b) LEISHEN C32151L; (c) ZVISION ML-30S
    Performance parametersVelodyne VLP16LEISHEN C32151LZVISION ML-30S
    Number of lines1632140
    Measuring range /m10015030
    Measuring accuracy /cm±3±2±3
    Vertical angle range /(°)303070
    Vertical angular resolution /(°)211
    Horizontal angle range /(°)360360150
    Horizontal angular resolution /(°)0.20.50.3
    Scanning frequency /Hz101010
    Table 1. Performance parameters of LiDAR
    LiDARAlgorithmTPAFNATTPAPPA
    Velodyne VLP16MBR81.245.3869.5684.44
    TPE81.245.3868.7683.13
    RDME81.245.3870.0385.56
    LEISHEN C32151LMBR81.806.8470.8386.93
    TPE81.806.8471.3487.28
    RDME81.806.8474.2390.91
    ZVISION ML-30SMBR80.375.5669.1686.05
    TPE80.375.5670.1787.62
    RDME80.375.5673.6894.19
    Table 2. Algorithm effect evaluation table unit: %
    Jie Hu, Han Liu, Wencai Xu, Liang Zhao. Position Detection Algorithm of Road Obstacles Based on 3D LiDAR[J]. Chinese Journal of Lasers, 2021, 48(24): 2410001
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