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    政大機構典藏 > 資訊學院 > 資訊科學系 > 會議論文 >  Item 140.119/137219


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    題名: Visual Navigation for UAVs Landing on Accessory Building Floor
    作者: 劉吉軒
    Liu, Jyishane
    Liu, Hsiao-Che
    貢獻者: 資科系
    關鍵詞: drone navigation;vision-based navigation;behavior tree;precision landing;building accessory floor
    日期: 2020-12
    上傳時間: 2021-09-22 10:38:31 (UTC+8)
    摘要: Landing is a critical step in most real world UAV applications, especially in delivery. A package delivery is successful only when a landing or a low-altitude drop-off (pseudo-landing) is completed. For precision landing requirement, vision-based navigation techniques are of high potential to be reliable and accurate. In this paper, we present a research work on autonomous visual navigation for precision landing on accessory building floor. We incorporate some state-of-the-art vision-based methods, develop other functional components to present an employable autonomous navigation system for precision landing near buildings. Initial experiments in a real world scenario show an encouraging results with high success rate of performing precision landing.
    關聯: Proceedings of the International Conference on Pervasive Artificial Intelligence 2020 (ICPAI 2020), Pervasive Artificial Intelligence Research Labs
    資料類型: conference
    DOI 連結: https://doi.org/10.1109/ICPAI51961.2020.00037
    DOI: 10.1109/ICPAI51961.2020.00037
    顯示於類別:[資訊科學系] 會議論文

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