Enhanced Obstacle Avoidance of Quadrotor UAV via Fuzzy FOPID Control and Deep learning based Observer

This paper proposes a novel hybrid method integrating a deep neural network based observer to detect obstacles in the quadrotor’s flight path with fuzzy logic based control and fractional order PID for sensitive missions requiring the ability to detect and avoid unexpected objects. The results of the simulations, which were executed using MATLAB 2023b, demonstrate how effective this strategy is in avoiding obstacles even when the UAV is carrying a load.