A probabilistic–geometric approach for UAV detection and avoidance systems

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dc.contributor.authorLee, Hae-In
dc.contributor.authorShin, Hyo-Sang
dc.contributor.authorTsourdos, Antonios
dc.date.accessioned2022-12-14T13:35:09Z
dc.date.available2022-12-14T13:35:09Z
dc.date.issued2022-11-27
dc.description.abstractThis paper proposes a collision avoidance algorithm for the detection and avoidance capabilities of Unmanned Aerial Vehicles (UAVs). The proposed algorithm aims to ensure minimum separation between UAVs and geofencing with multiple no-fly zones, considering the sensor uncertainties. The main idea is to compute the collision probability and to initiate collision avoidance manoeuvres determined by the differential geometry concept. The proposed algorithm is validated by both theoretical and numerical analysis. The results indicate that the proposed algorithm ensures minimum separation, efficiency, and scalability compared with other benchmark algorithms.en_UK
dc.description.sponsorshipEuropean Union funding: SJU/LC/342-CTR.en_UK
dc.identifier.citationLee HI, Shin HS, Tsourdos A. (2022) A probabilistic–geometric approach for UAV detection and avoidance systems, Sensors, Volume 22, Issue 23, November 2022, Article number 9230en_UK
dc.identifier.issn1424-8220
dc.identifier.urihttps://doi.org/10.3390/s22239230
dc.identifier.urihttps://dspace.lib.cranfield.ac.uk/handle/1826/18815
dc.language.isoenen_UK
dc.publisherMDPIen_UK
dc.rightsAttribution 4.0 International*
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/*
dc.subjectdetection and avoidanceen_UK
dc.subjectUnmanned Aerial Vehicle (UAV)en_UK
dc.subjectcollision probabilityen_UK
dc.subjectdifferential geometryen_UK
dc.titleA probabilistic–geometric approach for UAV detection and avoidance systemsen_UK
dc.typeArticleen_UK

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