Enhancing Autonomous Drone Navigation in Unfamiliar Environments with Predictive PID Control and Neural Network Integration
摘要
For the autonomous movement of drones in an unfamiliar environment containing potential obstacles, demanding precision and stability without compromising speed, we have introduced PID controller values in this paper. These values satisfy the condition of not surpassing coordinates to avoid collisions as a priority, while achieving stability and speed. Additionally, we have constructed a neural network using artificial intelligence to predict values, providing accuracy and predictive ability even amid changing parameters used to guide the drones. This approach empowers the drones to maintain energy efficiency, incorporating it with reinforcement learning-based path planning