Please use this identifier to cite or link to this item: https://ah.lib.nccu.edu.tw/handle/140.119/137219
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: Dec-2020
上傳時間: 22-Sep-2021
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: https://doi.org/10.1109/ICPAI51961.2020.00037
Appears in Collections:會議論文

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