In this work, we research and evaluate incremental hopping-window pose-graph fusion strategies for vehicle localization. Pose-graphs can model multiple absolute and relative vehicle localization sensors, and can be optimized using non-linear techniques. We focus on the performance of incremental hopping-window optimization for on- line usage in vehicles and compare it with global off-line optimization. Our evaluation is based on 180 Km long vehicle trajectories that are recorded in highway, urban, and rural areas, and that are accompanied with post-processed Real Time Kinematic GNSS as ground truth. The results exhibit a 17% reduction in the error's standard deviation and a significant reduction in GNSS outliers when compared with automotive-grade GNSS receivers. The incremental hopping-window pose- graph optimization bounds the computation cost, when compared to global pose-graph fusion, which increases linearly with the size of the pose- graph, whereas the difference in accuracy is only 1%. This allows real-time usage of non-linear pose-graph fusion for vehicle localization.


    Access

    Check access

    Check availability in my library

    Order at Subito €


    Export, share and cite



    Title :

    Incremental Hopping-Window Pose-Graph Fusion for Real-Time Vehicle Localization


    Contributors:


    Publication date :

    2019-04-01


    Size :

    8593512 byte





    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English




    Real-Time Pose Graph SLAM based on Radar

    Holder, Martin / Hellwig, Sven / Winner, Hermann | IEEE | 2019


    Pose Graph Fusion for Robot Follow Control

    Forstenhausler, Marc / Muller, Johannes / Dietmayer, Klaus | IEEE | 2021


    Vehicle self-localization based on initial pose

    HOLICKI MARCIN / RALF HETZEL / IKEN THOMAS et al. | European Patent Office | 2023

    Free access

    Pose-graph based 3D map fusion with distributed robot system

    Chen, Haoyao / Zhong, Jin / Fu, Yanling et al. | IEEE | 2014