Lee, Hae-InShin, Hyo-SangTsourdos, Antonios2022-12-142022-12-142022-11-27Lee 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 92301424-8220https://doi.org/10.3390/s22239230https://dspace.lib.cranfield.ac.uk/handle/1826/18815This 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.enAttribution 4.0 Internationaldetection and avoidanceUnmanned Aerial Vehicle (UAV)collision probabilitydifferential geometryArticle