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.

The authors declare no conflict of interest.

Not applicable

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.