A Probabilistic-Geometric Approach for UAV Detection and Avoidance Systems

Sensors (Basel). 2022 Nov 27;22(23):9230. doi: 10.3390/s22239230.

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.

Keywords: Unmanned Aerial Vehicle (UAV); collision probability; detection and avoidance; differential geometry.

MeSH terms

  • Algorithms*
  • Benchmarking*
  • Probability
  • Uncertainty