Acta Optica Sinica, Volume. 43, Issue 24, 2428003(2023)

HRegNet-LO: LiDAR Odometry Measurement Based on End-to-End Deep Neural Network

Yongjian Fu, Zongchun Li*, Hua He, Li Wang, and Cong Li
Author Affiliations
  • Institute of Geospatial Information, PLA Strategic Support Force Information Engineering University, Zhengzhou 450001, Henan , China
  • show less
    References(20)

    [1] Liu P F. High-precision vehicle GNSS/INS integrated navigation system aided by odometer[J]. Optics and Precision Engineering, 28, 979-987(2020).

    [2] Lu J, Liu Y H, Zhang R F. Semantic-based visual odometry towards dynamic scenes[J]. Laser & Optoelectronics Progress, 58, 0611001(2021).

    [3] Zhang Z T, Zhang R F, Liu Y H. Visual odometry algorithm based on deep learning[J]. Laser & Optoelectronics Progress, 58, 0415001(2021).

    [4] Qin Z, Gao X C, Chen Z K et al. Improved Lidar odometer based on motion prediction[J]. Laser & Optoelectronics Progress, 60, 1928004(2023).

    [6] Zhang J, Singh S. Low-drift and real-time lidar odometry and mapping[J]. Autonomous Robots, 41, 401-416(2017).

    [7] Shan T X, Englot B. LeGO-LOAM: lightweight and ground-optimized lidar odometry and mapping on variable terrain[C], 4758-4765(2019).

    [8] Park Y S, Jang H, Kim A. I-LOAM: intensity enhanced LiDAR odometry and mapping[C], 455-458(2020).

    [9] Geiger A, Lenz P, Urtasun R. Are we ready for autonomous driving? The KITTI vision benchmark suite[C], 3354-3361(2012).

    [10] Wang H, Wang C, Chen C L et al. F-LOAM: fast LiDAR odometry and mapping[C], 4390-4396(2021).

    [11] Shan T X, Englot B, Meyers D et al. LIO-SAM: tightly-coupled lidar inertial odometry via smoothing and mapping[C], 5135-5142(2021).

    [12] He X, Pan S G, Tan Y et al. Visual-inertial odometry and global navigation satellite system location algorithm based on point-line feature in outdoor scenes[J]. Laser & Optoelectronics Progress, 59, 1815002(2022).

    [13] Júnior G P C, Rezende A M C, Miranda V R F et al. EKF-LOAM: an adaptive fusion of LiDAR SLAM with wheel odometry and inertial data for confined spaces with few geometric features[J]. IEEE Transactions on Automation Science and Engineering, 19, 1458-1471(2022).

    [14] Besl P J, McKay N D. A method for registration of 3-D shapes[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 14, 239-256(1992).

    [15] Deschaud J E. IMLS-SLAM: scan-to-model matching based on 3D data[C], 2480-2485(2018).

    [16] Magnusson M, Lilienthal A, Duckett T. Scan registration for autonomous mining vehicles using 3D-NDT[J]. Journal of Field Robotics, 24, 803-827(2007).

    [17] Hong H, Lee B H. Probabilistic normal distributions transform representation for accurate 3D point cloud registration[C], 3333-3338(2017).

    [19] Lu F, Chen G, Liu Y L et al. HRegNet: a hierarchical network for large-scale outdoor LiDAR point cloud registration[C], 15994-16003(2022).

    Tools

    Get Citation

    Copy Citation Text

    Yongjian Fu, Zongchun Li, Hua He, Li Wang, Cong Li. HRegNet-LO: LiDAR Odometry Measurement Based on End-to-End Deep Neural Network[J]. Acta Optica Sinica, 2023, 43(24): 2428003

    Download Citation

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

    Category: Remote Sensing and Sensors

    Received: Feb. 14, 2023

    Accepted: Mar. 22, 2023

    Published Online: Dec. 12, 2023

    The Author Email: Li Zongchun (13838092876@139.com)

    DOI:10.3788/AOS230548

    Topics