Dead reckoning is a common navigation method in extraterrestrial rover missions. However, its effectiveness is often limited by the accumulated error from odometry, which can be mitigated through global localization techniques. We introduce a global localization method that utilizes horizon line matching with a digital elevation map (DEM) for a lunar rover equipped only with an RGB-D camera. The method consists of two main phases: generating a horizon line dataset by projecting the DEM onto a pose search network (PSN) and aligning horizon lines from individual poses with the actual horizon line captured by the rover's camera. Our approach employs feature-level matching instead of traditional pixel-level matching, significantly improving the stability and efficiency of the localization process. By adopting innovative segmentation and search strategies, we also reduce the computational complexity of curve matching. The effectiveness of our method is validated through high-fidelity lunar simulations, demonstrating superior localization accuracy compared to other DEM-based methods. Our approach presents a compelling solution for enhancing the navigation capabilities of lunar rovers with a limited sensor system.


    Access

    Check access

    Check availability in my library

    Order at Subito €


    Export, share and cite



    Title :

    Global Localization Technology of Lunar Rover by Horizon Line Matching


    Contributors:
    Tian, Zechuan (author) / Zhang, Hongying (author) / Hu, Quan (author)


    Publication date :

    2024-12-01


    Size :

    17766947 byte




    Type of media :

    Article (Journal)


    Type of material :

    Electronic Resource


    Language :

    English



    Lunar Rover Localization Using Craters as Landmarks

    Ono, M. / Ravichandar, S. / Swan, R. M. et al. | NTRS | 2022


    Lunar Rover Localization Using Craters as Landmarks

    Matthies, Larry / Daftry, Shreyansh / Tepsuporn, Scott et al. | ArXiv | 2022

    Free access

    Lunar Rover Localization Using Craters as Landmarks

    Matthies, Larry / Daftry, Shreyansh / Tepsuporn, Scott et al. | IEEE | 2022


    Lunar rover

    LIU QIANG / LI JIAN / LIU GANG et al. | European Patent Office | 2024

    Free access

    Lunar rover

    WU YANQING / JIAO FANWEI / XI CHAO | European Patent Office | 2020

    Free access