Semantic segmentation based mapping systems for the safe and precise landing of flying vehicles

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dc.contributor.authorDhami, Harsimret
dc.contributor.authorIgnatyev, Dmitry
dc.contributor.authorTsourdos, Antonios
dc.date.accessioned2023-06-26T09:36:27Z
dc.date.available2023-06-26T09:36:27Z
dc.date.issued2023-04-17
dc.description.abstractUnmanned Aerial Systems (UAS) are a promising technology for many areas, including transportation, agriculture, inspection, and rescue missions. However, to enable a high level of autonomy, including Beyond Visual Line of Sight (BVLOS) filght, the drones should be able to perform safe landings in unknown areas without an operator. Hence there is a need for development of safe landing methods for autonomous drones. The autonomous UAVs can often be operated more economically than the conventional manned aircraft. As technology advances, autonomous UAVs are expected to play an increasingly important role in a variety of industries and applications. In this paper we have explored a semantic segmentation-based approach for the problem of autonomous landing.en_UK
dc.identifier.citationDhami HS, Ignatyev D, Tsourdos A. (2022) Semantic segmentation based mapping systems for the safe and precise landing of flying vehicles, IFAC-PapersOnLine, Volume 55, Issue 22, 2022, pp. 310-315en_UK
dc.identifier.eissn2405-8963
dc.identifier.issn2405-8971
dc.identifier.urihttps://doi.org/10.1016/j.ifacol.2023.03.052
dc.identifier.urihttps://dspace.lib.cranfield.ac.uk/handle/1826/19888
dc.language.isoenen_UK
dc.publisherElsevieren_UK
dc.rightsAttribution-NonCommercial-NoDerivatives 4.0 International*
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/*
dc.subjectSemantic segmentationen_UK
dc.subjectComputer visionen_UK
dc.subjectAerial image segmentationen_UK
dc.subjectUnmanned aerial Vehicles (UAVs)en_UK
dc.subjectAutonomous Landingen_UK
dc.titleSemantic segmentation based mapping systems for the safe and precise landing of flying vehiclesen_UK
dc.typeArticleen_UK

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