A probabilistic–geometric approach for UAV detection and avoidance systems
Date published
2022-11-27
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MDPI
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Article
ISSN
1424-8220
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Citation
Lee 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 9230
Abstract
This 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.
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Github
Keywords
detection and avoidance, Unmanned Aerial Vehicle (UAV), collision probability, differential geometry
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Attribution 4.0 International
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Funder/s
European Union funding: SJU/LC/342-CTR.