We present our latest research in learning deep sensorimotor policies for agile, vision-based quadrotor flight. We show methodologies for the successful transfer of such policies from simulation to the real world. In addition, we discuss the open research questions that still need to be answered to improve the agility and robustness of autonomous drones toward human-pilot performance.


    Zugriff

    Zugriff prüfen

    Verfügbarkeit in meiner Bibliothek prüfen

    Bestellung bei Subito €


    Exportieren, teilen und zitieren



    Titel :

    Learning Agile, Vision-Based Drone Flight: From Simulation to Reality


    Weitere Titelangaben:

    Springer Proceedings in Advanced Robotics


    Beteiligte:
    Billard, Aude (Herausgeber:in) / Asfour, Tamim (Herausgeber:in) / Khatib, Oussama (Herausgeber:in) / Scaramuzza, Davide (Autor:in) / Kaufmann, Elia (Autor:in)

    Kongress:

    The International Symposium of Robotics Research ; 2022 ; Geneva, Switzerland September 25, 2022 - September 30, 2022



    Erscheinungsdatum :

    2023-03-08


    Format / Umfang :

    8 pages





    Medientyp :

    Aufsatz/Kapitel (Buch)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch




    Learing Agile, Vision-Based Drone Flight: From Simulation to Reality

    Scaramuzza, Davide / Kaufmann, Elia | British Library Conference Proceedings | 2022


    Deep Drone Racing: Learning Agile Flight in Dynamic Environments

    Kaufmann, Elia / Loquercio, Antonio / Ranftl, Rene et al. | BASE | 2018

    Freier Zugriff

    Vision-based drone autonomous flight device and method

    LEE HAE DONG | Europäisches Patentamt | 2021

    Freier Zugriff

    Drone Swarm "Agile Suppression" Tactics

    Feng, Yuanbo / Wang, Bingqie / Li, Zheng et al. | VDE-Verlag | 2022


    DRONE FLIGHT OPTIMIZATION USING DRONE-TO-DRONE PERMISSIONING

    DELANEY MARK / WARD BRETT / RESTREPO CONDE MELISSA et al. | Europäisches Patentamt | 2020

    Freier Zugriff