Please use this identifier to cite or link to this item: https://ah.lib.nccu.edu.tw/handle/140.119/137219
DC FieldValueLanguage
dc.contributor資科系
dc.creator劉吉軒
dc.creatorLiu, Jyishane
dc.creatorLiu, Hsiao-Che
dc.date2020-12
dc.date.accessioned2021-09-22T02:38:31Z-
dc.date.available2021-09-22T02:38:31Z-
dc.date.issued2021-09-22T02:38:31Z-
dc.identifier.urihttp://nccur.lib.nccu.edu.tw/handle/140.119/137219-
dc.description.abstractLanding 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.
dc.format.extent517592 bytes-
dc.format.mimetypeapplication/pdf-
dc.relationProceedings of the International Conference on Pervasive Artificial Intelligence 2020 (ICPAI 2020), Pervasive Artificial Intelligence Research Labs
dc.subjectdrone navigation; vision-based navigation; behavior tree; precision landing; building accessory floor
dc.titleVisual Navigation for UAVs Landing on Accessory Building Floor
dc.typeconference
dc.identifier.doi10.1109/ICPAI51961.2020.00037
dc.doi.urihttps://doi.org/10.1109/ICPAI51961.2020.00037
item.grantfulltextrestricted-
item.openairetypeconference-
item.fulltextWith Fulltext-
item.openairecristypehttp://purl.org/coar/resource_type/c_18cf-
item.cerifentitytypePublications-
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