LiDAR map-based localization and navigation play a crucial role in autonomous navigation, especially in GNSS-denied areas, by matching LiDAR data with a 3D point cloud map in real time. However, initiating localization from intermediate points on the map, distant from the origin, presents challenges. Typically, localization begins from the map’s origin, where algorithms can easily match current points to those near the origin. Challenges arise when starting from intermediate points, where the algorithm tries to match the current points’ features with those near the origin of the point cloud map. This mismatch can cause localization failure, leading to what is popularly known as the robot kidnapping problem. To tackle this challenge, we propose a solution involving the creation of unique nodes on the point cloud map by fusing LiDAR and GNSS data. Subsequently, live GNSS data is utilized to identify the nearest node, and the corresponding initial pose is published to initiate the localization problem at intermediate points on the map. Extensive real-time testing of this algorithm has been conducted at the IIT Hyderabad campus. The code for the same will be released at: https://github.com/Rakshith-Ram/Localize_Anywhere


    Access

    Check access

    Check availability in my library

    Order at Subito €


    Export, share and cite



    Title :

    LiDAR-GNSS Fusion to Initiate Localization at Intermediate Points on a 3D Point Cloud Map


    Contributors:


    Publication date :

    2024-10-07


    Size :

    8422383 byte





    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English



    GNSS NLOS Exclusion Based on Dynamic Object Detection Using LiDAR Point Cloud

    Wen, Weisong Weisong / Zhang, Guohao / Hsu, Li-Ta | IEEE | 2021


    Identification of planar points in lidar point cloud obtained with vehicle lidar system

    HU YAO / DU XINYU / ZHANG WENDE et al. | European Patent Office | 2025

    Free access

    IDENTIFICATION OF PLANAR POINTS IN LIDAR POINT CLOUD OBTAINED WITH VEHICLE LIDAR SYSTEM

    HU YAO / DU XINYU / ZHANG WENDE et al. | European Patent Office | 2023

    Free access

    Improved LiDAR Probabilistic Localization for Autonomous Vehicles Using GNSS

    Miguel Paraiso, Miguel Ángel de / García Fernández, Fernando / Armingol Moreno, José María | BASE | 2020

    Free access

    IDENTIFICATION OF EDGE POINTS AND PLANAR POINTS IN POINT CLOUD OBTAINED BY VEHICLE LIDAR SYSTEM

    HU YAO / DU XINYU / ZHANG WENDE et al. | European Patent Office | 2023

    Free access