For autonomous vehicles, high-precision real-time localization is the guarantee of stable driving. Compared with the visual odometry (VO), the LiDAR odometry (LO) has the advantages of higher accuracy and better stability. However, 2D LO is only suitable for the indoor environment, and 3D LO has less efficiency in general. Both are not suitable for the online localization of an autonomous vehicle in an outdoor driving environment. In this paper, a direct LO method based on the 2.5D grid map is proposed. The fast semi-dense direct method proposed for VO is employed to register two 2.5D maps. Experiments show that this method is superior to both the 3D-NDT and LOAM in the outdoor environment.


    Zugriff

    Zugriff prüfen

    Verfügbarkeit in meiner Bibliothek prüfen

    Bestellung bei Subito €


    Exportieren, teilen und zitieren



    Titel :

    DLO: Direct LiDAR Odometry for 2.5D Outdoor Environment


    Beteiligte:
    Sun, Lu (Autor:in) / Zhao, Junqiao (Autor:in) / He, Xudong (Autor:in) / Ye, Chen (Autor:in)


    Erscheinungsdatum :

    01.06.2018


    Format / Umfang :

    3615182 byte




    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



    DLO: DIRECT LIDAR ODOMETRY FOR 2.5D OUTDOOR ENVIRONMENT

    Sun, Lu / Zhao, Junqiao / He, Xudong et al. | British Library Conference Proceedings | 2018


    2.5D vehicle odometry estimation

    Ciarán Eising / Leroy‐Francisco Pereira / Jonathan Horgan et al. | DOAJ | 2022

    Freier Zugriff

    2.5D vehicle odometry estimation

    Eising, Ciarán / Pereira, Leroy‐Francisco / Horgan, Jonathan et al. | Wiley | 2022

    Freier Zugriff

    DL-SLAM: DIRECT 2.5D LIDAR SLAM FOR AUTONOMOUS DRIVING

    Li, Jun / Zhao, Junqiao / Kang, Yuchen et al. | British Library Conference Proceedings | 2019


    DL-SLAM: Direct 2.5D LiDAR SLAM for Autonomous Driving

    Li, Jun / Zhao, Junqiao / Kang, Yuchen et al. | IEEE | 2019