Addressing the challenge of roadside litter in the United States, which has traditionally relied on costly and ineffective manual cleanup methods11https://www.conserve-energy-future.com/littering-effects-humans-animals-environment.php, this paper presents an autonomous multi-robot system for highway litter monitoring and collection. Our solution integrates an aerial vehicle to scan and gather data across highway stretches with a terrestrial robot equipped with a Convolutional Neural Network (CNN) for litter detection and mapping. Upon detecting litter, the ground robot navigates to each pinpointed location, re-assesses the vicinity, and employs a “greedy pickup” approach to address potential mapping inaccuracies or litter misplacements. Through simulation studies and real-world robotic trials, this work highlights the potential of our proposed system for highway cleanliness and management in the context of Robotics, Automation, and Artificial Intelligence.


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    Titel :

    TRASH: Tandem Rover and Aerial Scrap Harvester


    Beteiligte:
    Milburn, Lee (Autor:in) / Chiaramonte, John (Autor:in) / Fenton, Jack (Autor:in) / Padir, Taskin (Autor:in)


    Erscheinungsdatum :

    14.12.2023


    Format / Umfang :

    5500684 byte




    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



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