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• W2924538845 abstract "The capability of landing on previously unvisited areas is a fundamental challenge for an unmanned aerial vehicle (UAV). In this paper, we developed a vision-based motion estimation as an aid to improve landing performance. As an alternative to the common scenarios accompanying by external infrastructures or well-defined marker, the proposed hybrid framework can successfully land on a new area without any prior information about guiding marks. The implementation was based on the optical flow technique associated with a multi-scale strategy to overcome the decreasing field-of-view during the UAV descending. Compared with a commercial Global Positioning System (GPS) through a sequence of flight trials, the vision-aided scheme can effectively minimize the possible sensing error, thus, leading to a more accurate result. Moreover, this work has potential to integrate the fast-growing image learning process and yields more practical versatility for UAV applications in the future." @default.
• W2924538845 created "2019-04-01" @default.
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• W2924538845 date "2019-03-20" @default.
• W2924538845 modified "2023-10-16" @default.
• W2924538845 title "Motion Estimation by Hybrid Optical Flow Technology for UAV Landing in an Unvisited Area" @default.
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• W2924538845 doi "https://doi.org/10.3390/s19061380" @default.
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