Onboard Drone Detection with Event Cameras

Master thesis (2022)

Authors

A. Barberia Chueca Aerospace Engineering

Contributors

J.J.G. Dupeyroux (mentor)
G.C.H.E. de Croon (graduation committee member)
Faculty
Aerospace Engineering, Aerospace Engineering
Copyright: © 2022 Alejandro Barberia Chueca
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Published Date

14-07-2022

Language

English

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Faculty

Aerospace Engineering

Abstract

In an effort to develop a new relative sensing method for drone swarms, the suitability of event cameras is assessed for propeller detection. Benchmark tests were conducted for different propellers under different lighting and background conditions, varying the observation distance and spinning frequency. The different tests were evaluated on event count, frequency, and clustering, as these are the most characteristic properties of the propeller-generated signal. A propeller detection metric was derived as a fuzzy classifier to assess detectability. It was observed that the sensor employed is limiting the detection range due to low resolution, with a maximum detection range of 75 cm. While at low spinning frequencies it is possible to detect the propeller at such distance, for higher frequences (6000 to 8000 RPMs) the range decreases to 45 cm for the tests with highest blade to background contrast and two-blade propellers. It was observed that lower contrasts reduce the successful detections only to low frequencies, and three-blade propellers become completely indetectable due to the static overlap between the blades. Therefore, it is concluded that, at this stage of the technology, the use case of event cameras for relative sensing is constrained to close distances with high contrast.