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- W3168082187 abstract "This paper presents an approach for image-based detection of clouds on-board unmanned aerial vehicles (UAVs), taking into account changing environmental conditions and different sensor types. Therefore, different image processing methods for cloud detection are introduced. In order to separate manned and unmanned aircraft in airspaces where air traffic is expected to operate according to visual flight rules (VFR), the visibility of unmanned platforms must be ensured. Besides reduced visibility, clouds can additionally indicate an increased risk of icing and turbulence. Thus, entry into clouds must be prevented and the required minimum distances to clouds have to be complied with. In order to initiate appropriate evasive maneuvers, the cloud detection component as part of a Sense and Avoid system must deliver robust results. Our previous investigations on cloud detection algorithms have shown that the quality of the results depends very much on environmental conditions like lighting conditions, visibility, cloud type or ground texture. The requirement to deliver reliable detection results under as many weather scenarios as possible is therefore difficult to fulfill. This goal shall be achieved by using different sensor configurations and a performance-based selection of cloud detection algorithms. Apart from introducing this concept of adaptive and context-sensitive cloud detection, this paper gives an overview of complementing cloud detection methods that can be used for this purpose." @default.
- W3168082187 created "2021-06-22" @default.
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- W3168082187 date "2021-03-06" @default.
- W3168082187 modified "2023-10-07" @default.
- W3168082187 title "Cloud Detection System for UAV Sense and Avoid: Discussion of Suitable Algorithms" @default.
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- W3168082187 doi "https://doi.org/10.1109/aero50100.2021.9438181" @default.
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