Visual-inertial navigation system (VINS) is widely used for autonomous platforms but suffers from drifting over a long time. To remedy this situation, a lightweight 3D prior map-aided visual-inertial navigation system is presented in this paper, which tightly couples the visual-inertial data stream with a lightweight prior map involving 3D line information. To fill the gaps between 3D maps and 2D images, the mutual geometric feature of line segments is utilized to connect these two types of information in different dimensions. By detecting and matching line features in two data sources, the line pairs are utilized as constraints in the nonlinear optimization model and added to the existing factor graph framework in a tightly coupled form. Meanwhile, a fast line feature tracking strategy is employed to monitor and remove extreme outliers, which will further improve the reliability of this structural characteristic during the cross-modality localization. The effectiveness of the proposed method is evaluated by public indoor unmanned aerial vehicles (UAV) datasets, and outdoor unmanned ground vehicles (UGV) datasets generated by the CARLA simulator.


    Zugriff

    Zugriff prüfen

    Verfügbarkeit in meiner Bibliothek prüfen

    Bestellung bei Subito €


    Exportieren, teilen und zitieren



    Titel :

    Tightly-coupled Line Feature-aided Visual Inertial Localization within Lightweight 3D Prior Map for Intelligent Vehicles


    Beteiligte:
    Zheng, Xi (Autor:in) / Wen, Weisong (Autor:in) / Hsu, Li-Ta (Autor:in)


    Erscheinungsdatum :

    24.09.2023


    Format / Umfang :

    1001248 byte





    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



    Tightly Coupled Stereo Vision Aided Inertial Navigation Using Continuously Tracked Features for Land Vehicles

    Liu, Fei / Sarvrood, Yashar Balazadegan / Gao, Yang | British Library Conference Proceedings | 2015


    Visual-Inertial Tightly Coupled Fusion and Nonlinear Optimization for UAVs Navigation

    You, Zhenxing / Cai, Zhihao / Zhao, Jiang et al. | British Library Conference Proceedings | 2018



    Tightly-coupled monocular visual-inertial fusion for autonomous flight of rotorcraft MAVs

    Shen, Shaojie / Michael, Nathan / Kumar, Vijay | IEEE | 2015