Research on logistics of intelligent unmanned aerial vehicle integration system

As Unmanned Aerial Vehicle (UAV) is more and more frequently used in farming and logistics, civil and military alike, researches involving UAVs also starts to boom. In the civil field, UAV is generally flown in urban areas, so buildings are the main factors hindering the normal flight of UAV. Therefore, it is necessary to calculate an optimal flight path of UAV under constraints. The intelligent logistics UAV proposed in this paper can be used to replace special couriers to deliver small goods. It is a quadcopter integrated with a webcam, ultrasound Ground Proximity Warning System (GPWS), and is controllable through a mobile APP. Gradient descent algorithm, Linear Quadratic Regulator (LQR) and improved Proportion-Integral-Derivative (PID) controllers are applied in its flight control system, MATLAB and wavelet transform to handle fuzzy image. In addition, ant colony algorithm and adaptive strategies are used in the path planning process. As a result, it can detect surrounding obstacles in-flight, and the ground control station can receive feedback information and prepare for emergency operations.