This paper introduces a new approach to achieving autonomous soft-landing of an unmanned aerial vehicle (UAV) on a moving platform. The proposed method incorporates terminal constraints on position, velocity, and acceleration by utilizing a minimum jerk-based guidance strategy. An optimal landing time is computed using an acceleration-minimizing cost function. Software-in-the-loop simulations are conducted using the PX4-ROS2-Gazebo environment to demonstrate successful landing on a moving platform. The results indicate that the proposed strategy generates smooth trajectories, enabling the UAV to autonomously achieve soft-landing on the moving platform, even when perturbations in the platform's motion are introduced.


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    Titel :

    Minimum Jerk Guidance for Autonomous Soft-Landing of an Unmanned Aerial Vehicle on a Moving Platform


    Beteiligte:


    Erscheinungsdatum :

    12.12.2024


    Format / Umfang :

    1420916 byte





    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



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