Laser & Optoelectronics Progress, Volume. 60, Issue 22, 2228002(2023)

LiDAR Ground-Segmentation Algorithm Based on Slope Threshold and Convolution Filtering Processing

Tao Shangguan1, Rong Xie1、*, Zufang Lei2, and Zheng Liu1
Author Affiliations
  • 1National Key Laboratory of Radar Signal Processing, Xidian University, Xi'an 710071, Shaanxi , China
  • 2Shenzhen Leishen Intelligent System Co., Ltd., Shenzhen 518100, Guangdong , China
  • show less
    References(16)

    [1] Huang S Y, Liu L M, Dong J et al. A review of ground filtering algorithms for vehicle LiDAR scan point cloud data[J]. Opto-Electronic Engineering, 47, 3-14(2020).

    [2] Bekey G A. Springer handbook of robotics (B. siciliano and O. khatib; 2008)[book review][J]. IEEE Robotics & Automation Magazine, 15, 110(2008).

    [3] Asvadi A, Peixoto P, Nunes U. Detection and tracking of moving objects using 2.5D motion grids[C], 788-793(2015).

    [4] Li Q Q, Zhang L, Mao Q Z et al. Motion field estimation for a dynamic scene using a 3D LiDAR[J]. Sensors, 14, 16672-16691(2014).

    [5] Li L, Yang F, Zhu H et al. An improved RANSAC for 3D point cloud plane segmentation based on normal distribution transformation cells[J]. Remote Sensing, 9, 433(2017).

    [6] Hermas D, Izzet I, Papanikolopoulos N. Fast segmentation of 3D point clouds: a paradigm on LiDAR data for autonomous vehicle applications[C], 5067-5073(2017).

    [7] Narksri P, Takeuchi E, Ninomiya Y et al. A slope-robust cascaded ground segmentation in 3D point cloud for autonomous vehicles[C], 497-504(2018).

    [8] Mei S M, Huang M H, Liu Z H et al. The ground segmentation method in complex scenes based on three-dimensional lidar[J]. Laser & Optoelectronics Progress, 59, 1028003(2022).

    [9] Feng S Q, Hua X H, Duan C W et al. An adaptive slope threshold method for ground -point cloud segmentation[J]. Science of Surveying and Mapping, 46, 156-161(2021).

    [10] Zhang K, Yu C L, Zhao Y L et al. Research on a ground segmentation algorithm based on adaptive thresholds for 3D laser point clouds[J]. Automotive Engineering, 43, 1005-1012(2021).

    [11] Bogoslavskyi I, Stachniss C. Efficient online segmentation for sparse 3D laser scans[J]. PFG-Journal of Photogrammetry, Remote Sensing and Geoinformation Science, 85, 41-52(2017).

    [12] Shen Z H, Liang H W, Lin L L et al. Fast ground segmentation for 3D LiDAR point cloud based on jump-convolution-process[J]. Remote Sensing, 13, 3239(2021).

    [13] Guo C Z, Sato W, Han L et al. Graph-based 2D road representation of 3D point clouds for intelligent vehicles[C], 715-721(2011).

    [14] Charles R Q, Hao S, Mo K C et al. PointNet: deep learning on point sets for 3D classification and segmentation[C], 77-85(2017).

    [15] Lang A H, Vora S, Caesar H et al. PointPillars: fast encoders for object detection from point clouds[C], 12689-12697(2020).

    [16] Shi Y Z. Obstacle target detection and tracking based on 3D LiDAR[D](2020).

    Tools

    Get Citation

    Copy Citation Text

    Tao Shangguan, Rong Xie, Zufang Lei, Zheng Liu. LiDAR Ground-Segmentation Algorithm Based on Slope Threshold and Convolution Filtering Processing[J]. Laser & Optoelectronics Progress, 2023, 60(22): 2228002

    Download Citation

    EndNote(RIS)BibTexPlain Text
    Save article for my favorites
    Paper Information

    Category: Remote Sensing and Sensors

    Received: Jan. 12, 2023

    Accepted: Feb. 16, 2023

    Published Online: Nov. 6, 2023

    The Author Email: Rong Xie (rxie@mail.xidian.edu.cn)

    DOI:10.3788/LOP230491

    Topics