Kalman filtering is indispensable in UAV’s vision-based autonomous landing. However, Extended Kalman Filter(EKF) currently employed is increasingly unable to meet the rising requirements. EKF lacks in convergence performance and robustness. To address this issue, we introduces a more effective nonlinear Kalman filter, Invariant extended Kalman Filter (IEKF), into the step of tracking and locating cooperative target. We conducted simulation with Gazebo to verify the improvement of landing performance using IEKF. The use of IEKF has reduced the positional deviation by 85.28% and landing orientation by 41.15% compared to extended Kalman Filter(EKF). To further validate the conclusion, the real flight validation was also conducted.


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    Title :

    Vision-Based UAV Precision Landing via Invariant Extended Kalman Filtering


    Additional title:

    Lect. Notes Electrical Eng.


    Contributors:
    Yan, Liang (editor) / Duan, Haibin (editor) / Deng, Yimin (editor) / Fu, Yiqi (author) / Dang, Qingqing (author) / Zhao, Wen (author) / Li, Liqiao (author) / Zhu, Zhu (author)

    Conference:

    International Conference on Guidance, Navigation and Control ; 2024 ; Changsha, China August 09, 2024 - August 11, 2024



    Publication date :

    2025-03-08


    Size :

    11 pages





    Type of media :

    Article/Chapter (Book)


    Type of material :

    Electronic Resource


    Language :

    English




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