Autonomous navigation in dynamic environments is a nowadays unsolved challenge. Several approaches have been proposed to solve it, but they either have a low success rate, do not consider robot kinodynamic constraints or are not able to navigate through big scenarios where the known map information is needed. In this work, a previously existing planner, the Strategy-based Dynamic Object Velocity Space, S-DOVS, is modified and adapted to be included in a full navigation stack, with a localization system, an obstacle tracker and a global planner. The result is a system that is able to navigate successfully in real-world scenarios, where it may face complex challenges as dynamic obstacles or replanning. The final work is exhaustively tested in simulation and in a ground robot.


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    Titel :

    Full-stack S-DOVS: Autonomous Navigation in Complete Real-World Dynamic Scenarios


    Weitere Titelangaben:

    Lect. Notes in Networks, Syst.


    Beteiligte:
    Tardioli, Danilo (Herausgeber:in) / Matellán, Vicente (Herausgeber:in) / Heredia, Guillermo (Herausgeber:in) / Silva, Manuel F. (Herausgeber:in) / Marques, Lino (Herausgeber:in) / Martínez, Diego (Autor:in) / Riazuelo, Luis (Autor:in) / Montano, Luis (Autor:in)

    Kongress:

    Iberian Robotics conference ; 2022 ; Zaragoza, Spain November 23, 2022 - November 25, 2022



    Erscheinungsdatum :

    2022-11-19


    Format / Umfang :

    12 pages





    Medientyp :

    Aufsatz/Kapitel (Buch)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch




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