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Updated: Aug 17, 2025

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A Probabilistic-Geometric Approach for UAV Detection and Avoidance Systems.

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  • 1School of Aerospace, Transport and Manufacturing, Cranfield University, College Road, Cranfield MK43 0AL, UK.

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Summary
This summary is machine-generated.

This study introduces a novel collision avoidance algorithm for Unmanned Aerial Vehicles (UAVs), enhancing safety through precise separation and geofencing. The algorithm effectively manages sensor uncertainties for reliable drone navigation.

Keywords:
Unmanned Aerial Vehicle (UAV)collision probabilitydetection and avoidancedifferential geometry

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Area of Science:

  • Aerospace Engineering
  • Robotics
  • Control Systems

Background:

  • Unmanned Aerial Vehicles (UAVs) require robust collision avoidance systems for safe operation.
  • Ensuring minimum separation and adherence to geofenced no-fly zones is critical for UAVs.
  • Sensor uncertainties pose a significant challenge to reliable UAV navigation and collision detection.

Purpose of the Study:

  • To propose a novel collision avoidance algorithm for Unmanned Aerial Vehicles (UAVs).
  • To ensure minimum separation between UAVs and geofencing with multiple no-fly zones, accounting for sensor uncertainties.
  • To enhance the detection and avoidance capabilities of UAVs.

Main Methods:

  • Collision probability computation based on sensor data.
  • Utilization of differential geometry concepts for collision avoidance maneuvers.
  • Validation through comprehensive theoretical and numerical analysis.

Main Results:

  • The proposed algorithm effectively ensures minimum separation between UAVs.
  • Demonstrated efficiency and scalability in collision avoidance scenarios.
  • Successful integration with geofencing and no-fly zone constraints.

Conclusions:

  • The developed algorithm provides a reliable solution for UAV collision avoidance.
  • It offers superior performance in terms of safety, efficiency, and scalability compared to existing methods.
  • The approach is well-validated and suitable for real-world UAV applications.