A National Aeronautics and Space Administration (NASA) project developing computer vision algorithms for autonomous flight is producing real-world datasets with cameras mounted on aircraft. In related domains, such as autonomous driving, open datasets are key to innovation and advancement in computer vision and autonomous perception for future Advanced Air Mobility (AAM) operations. Few vision datasets, however, are publicly available in the aviation context. This paper introduces preliminary datasets containing several examples of approach and landing scenarios. The platform aircraft include a multirotor small unmanned aerial system (sUAS) and a crewed helicopter as surrogates for future electric vertical take-off and landing (eVTOL) aircraft. The dataset provides video imagery with associated inertial navigation system-global positioning system (INS-GPS) position and attitude estimates and other sensors. Surveyed locations of the visual features of the landing area are included. This dataset is the first to be released in an ongoing effort to collect and share large, diverse datasets relevant to autonomous aviation; community critique that can inform and improve future flight campaigns is welcome.


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    Titel :

    Visual and Inertial Datasets for an eVTOL Aircraft Approach and Landing Scenario


    Beteiligte:
    Nelson Brown (Autor:in) / Evan Kawamura (Autor:in) / Luke Bard (Autor:in) / A. J. Jaffe (Autor:in) / Wayne Ringelberg (Autor:in) / Keerthana Kannan (Autor:in) / Corey Ippolito (Autor:in)

    Kongress:

    AIAA SciTech Forum ; 2024 ; Orlando, FL, US


    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Keine Angabe


    Sprache :

    Englisch


    Schlagwörter :


    Visual & Inertial Datasets for an eVTOL Aircraft Approach and Landing Scenario

    Brown, Nelson / Kawamura, Evan / Bard, Luke et al. | AIAA | 2024


    Visual and Inertial Datasets for an eVTOL Aircraft Approach and Landing Scenario

    Nelson Brown / Evan Kawamura / Luke Bard et al. | NTRS


    Infrared-Constellation-Aided Landing of eVTOL Aircraft

    Brown, Aaron / Akagi, David / Reid, Ian et al. | AIAA | 2025


    EVTOL AIRCRAFT

    NEWMAN GLEN | Europäisches Patentamt | 2025

    Freier Zugriff

    EVTOL aircraft take-off and landing performance test system

    LIU JUANXIA / LIN QING / SONG SO-HEE et al. | Europäisches Patentamt | 2025

    Freier Zugriff