Reinforcement Learning for Autonomous UAV Navigation and Object Tracking in UE4 and AirSim

This article presents the implementation of a reinforcement learning algorithm for autonomous UAV navigation and object tracking in UE4 and AirSim. By leveraging the capabilities of these environments, the algorithm enables the UAV to learn how to navigate and track objects on its own, without requiring manual control. The results demonstrate the effectiveness of the RL model in enabling UAVs to perform complex tasks with minimal human intervention.