When generating 3D maps with unmanned aerial vehicles (UAVs) in GPS-denied environments, it is important to correctly handle path planning, estimation, and mapping techniques. Because multirotor UAVs are limited in flight time, using multiple UAVs to map an environment collaboratively can significantly improve the mapping efficiency. This paper addresses the following key issues required to enable mapping with multiple agents: Combining a reactive path planner with an obstacle avoidance algorithm to handle navigation in complex environments. Estimating the relative and global states of a UAV separately with a relative navigation framework to allow for loop closures in the mapping process without causing the estimation to diverge. Adapting a graph-based simultaneous localization and mapping (graph-SLAM) technique for multiple UAVs flying simultaneously and merging their maps in real-time. We were able to use these strategies to generate dense maps in complex GPS-denied environments with multiple UAVs.


    Access

    Check access

    Check availability in my library

    Order at Subito €


    Export, share and cite



    Title :

    Multi-Agent Mapping and Navigation of Unknown GPS-Denied Environments Using a Relative Navigation Framework


    Contributors:


    Publication date :

    2020-09-01


    Size :

    5026799 byte





    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English



    Formation Design for Optimal Relative Navigation in GPS Denied Environments

    Shoop, Timothy / Munoz, Josue / Gunther, Jacob et al. | Springer Verlag | 2023


    FORMATION DESIGN FOR OPTIMAL RELATIVE NAVIGATION IN GPS DENIED ENVIRONMENTS

    Shoop, Timothy / Munoz, Josue / Gunther, Jacob et al. | Springer Verlag | 2024



    Relative navigation approach for vision-based aerial GPS-denied navigation

    Leishman, Robert C. / McLain, Timothy W. / Beard, Randal W. | IEEE | 2013


    UAV Waypoint Opportunistic Navigation in GNSS-Denied Environments

    Yang, Yanhao / Khalife, Joe / Morales, Joshua J. et al. | IEEE | 2022