To boost the autonomy of Unmanned Aerial Vehicles (UAVs), this research focuses on creating a reliable solution to the Simultaneous Localization and Mapping (SLAM) problem. The idea of a novel filter-based on Smooth Variable Structure Filter (SVSF) as opposed to Extended Kalman Filter (EKF) to tackle the Inertial Navigation Systems (INS)/3D laser UAV navigation problem is the work’s original contribution. To show the benefits of hybrid SVSF localization over an EKF-based localization technique, simulation results for a 3D flight scenario are shown. The innovative form of SVSF is suggested as an alternative to improve the trade-off between robustness and optimality of UAV navigation. This second method yields reliable estimation results while making no assumptions about the noise properties. In addition, a new SLAM technique with high robustness against face parameter uncertainties and modeling errors is suggested in this study. The collected results support the efficiency of the SVSF strategy in comparison to EKF in experimental scenarios conducted under realistic conditions.


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    Title :

    Unmanned Aerial Vehicle Localization Using an Advanced Technique Based on the Smooth Variable Structure Filter


    Additional title:

    Lect. Notes Electrical Eng.



    Conference:

    International Conference on Electrical Engineering and Control Applications ; 2022 ; Khenchela, Algeria November 15, 2022 - November 17, 2022



    Publication date :

    2024-10-01


    Size :

    16 pages





    Type of media :

    Article/Chapter (Book)


    Type of material :

    Electronic Resource


    Language :

    English




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