Autonomous docking for underwater drones is crucial for various marine applications. This paper introduces an approach to autonomous underwater vehicle (AUV) docking using ArUco marker-based localization, as demonstrated by Project MIRA, at the Tau Autonomy Center, Norway. The method combines a control system with dual-feed computer vision based perception to achieve autonomy. The control system is based on a cascaded PID controller fine-tuned using various external sensors and optimization techniques. The vision system utilizes ArUco markers for 3D positioning. Our method uses visual markers to help the drone navigate to a custom docking pad. We achieved stable and reliable docking by combining advanced control systems using visual-inertial sensors. This work highlights the potential of using visual markers and smart control systems for underwater drone operations.


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    Title :

    Autonomous Docking for Underwater Drones Using ArUco Marker Based Localization


    Contributors:


    Publication date :

    2024-12-19


    Size :

    825741 byte




    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English



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