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10.1145/3476124.3488630acmconferencesArticle/Chapter ViewAbstractPublication Pagessiggraph-asiaConference Proceedingsconference-collections
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Training to Get a Drone License, Virtually

Published: 14 December 2021 Publication History
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  • Abstract

    We propose a drone flight training system (DFT MR) with a novel mixed reality (MR) technique to lower the risk of drone crashes for drone flight beginners and enhance their actual feelings of drone control. Recently, virtual reality (VR) or augmented reality (AR) has been widely employed in training systems. However, the current drone training systems in AR usually lack physical feedback from wind or air resistance. In addition, the VR training environment and the real world were considered to be inequivalent. The proposed MR system integrates the advantages of both VR and AR by transmitting the high-fidelity simulated physical control feedback, such as obstacle collision and wind influence, from VR to the MR device. The system not only benefits those who have VR sickness but also provides novice drone operators virtual crash-free drones for training to get their drone licenses.

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    References

    [1]
    CHANG, E., KIM, H.T., and YOO, B. 2020. Virtual Reality Sickness: A Review of Causes and Measurements. International Journal of Human–Computer Interaction 36, 1658-1682.
    [2]
    GO, Y.-G., LEE, J.-W., KANG, H.-S., and CHOI, S.-M. 2020. Interactive Training of Drone Flight Control in Mixed Reality. In Proceedings of the SIGGRAPH Asia 2020 XR, Virtual Event, Republic of Korea2020 Association for Computing Machinery, Article 11.
    [3]
    KIM, D.-H., GO, Y.-G., and CHOI, S.-M. 2018. First-person-view drone flying in mixed reality. In Proceedings of the SIGGRAPH Asia 2018 Posters, Tokyo, Japan2018 Association for Computing Machinery, Article 43.
    [4]
    Read, J.M. and Saleem, J.J. 2017. Task Performance and Situation Awareness with a Virtual Reality Head-Mounted Display. Proceedings of the Human Factors and Ergonomics Society Annual Meeting 61, 1, 2105–2109.

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    Published In

    cover image ACM Conferences
    SA '21 Posters: SIGGRAPH Asia 2021 Posters
    December 2021
    87 pages
    ISBN:9781450386876
    DOI:10.1145/3476124
    • Editors:
    • Shuzo John Shiota,
    • Ayumi Kimura,
    • Wan-Chun Alex Ma
    Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for third-party components of this work must be honored. For all other uses, contact the Owner/Author.

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    Association for Computing Machinery

    New York, NY, United States

    Publication History

    Published: 14 December 2021

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    • Poster
    • Research
    • Refereed limited

    Funding Sources

    • the Ministry of Science and Technology of Taiwan
    • the Ministry of Science and Technology of Taiwan

    Conference

    SA '21
    Sponsor:
    SA '21: SIGGRAPH Asia 2021
    December 14 - 17, 2021
    Tokyo, Japan

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    Overall Acceptance Rate 178 of 869 submissions, 20%

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