Autodocking is a sophisticated technology that allows drones to land automatically at a predetermined docking station. Computer vision plays an important role in the drone autodocking system, allowing the drone to "see" the intended object. The problem with drone control is the precision of determining and placing objects, in this case docking, where there is still a difference or error between the desired docking set point. The solution proposed in this article is to use the PID Controller (Proportional-Integral-Derivative Controller) algorithm. By using a PID controller, the drone can regulate its movements more precisely, maintain stability, and ensure proper landing. The results achieved using this approach, reached a 90% success rate (precision) with control of several environmental parameters. first page. The abstract contains a summary of backgrounds, methods, and research results, with the maximum number of characters being 150.


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    Titel :

    Autonomous Navigation onto Autodocking Drone System using Computer Vision


    Beteiligte:


    Erscheinungsdatum :

    2025




    Medientyp :

    Aufsatz (Zeitschrift)


    Format :

    Elektronische Ressource


    Sprache :

    Unbekannt




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