The fusion framework based on Light Detection and Ranging (LiDAR) and vision is susceptible to environmental constraints. Therefore, they are unable to adapt to complex and challenging environments. In response to this, this paper proposes a tightly coupled framework based on Global Navigation Satellite System (GNSS) data, which tightly couples GNSS, inertial, LiDAR and visual data. The experimental results demonstrate that, using publicly available challenging environment datasets, the proposed fusion system can achieve a 52.68% improvement in positioning accuracy compared to some existing fusion algorithms.


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    Titel :

    GVIL: Tightly Coupled GNSS-Visual-Inertial-Lidar for Position Estimation in Challenging Environments


    Beteiligte:
    Shi, Yanfang (Autor:in) / Lian, Baowang (Autor:in) / Zeng, Yonghong (Autor:in) / Kurniawan, Ernest (Autor:in) / Ma, Yugang (Autor:in)


    Erscheinungsdatum :

    24.06.2024


    Format / Umfang :

    1209671 byte





    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch