Research on Logistics Intelligent Unmanned Aerial Vehicle Combined Facial Recognition

As unmanned aerial vehicle (UAV) starts to be frequently used in the fields of industry, agriculture, reconnaissance and logistics, flight research involving UAV also starts to cover a wider range. In the civil field, UAV is generally used as an auxiliary tool to deal with urban problems, but buildings are the main factors hindering the flight of UAV. The intelligent logistics UAV proposed in this paper is used to replace the courier to deliver small goods and process the fuzzy images taken along the way. It is a quad copter implementation plan integrating flight control, obstacle avoidance ultrasound, mobile APP control system and webcam. Gradient descent algorithm and Proportion-Integral-Differential (PID) controller are applied in UAV flight control system, MATLAB and wavelet transform to handle fuzzy image. Compared with the traditional PID controller, the improved PID controller eliminates the steady-state error and reduces the lag effect caused by the integral link. The denoising effect of wavelet transform is better than the traditional median filter and mean filter. The UAV can detect surrounding obstacles during flight, and the ground control station receives feedback information and makes emergency treatment to ensure safe flight.

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The authors declare no conflict of interest.

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The datasets used in this study are openly available at [repository link] and the source code is available on GitHub at [GitHub link].

This work did not receive any external funding.