Advancing Autonomous UAVs: Safe Navigation and Object Avoidance in Dynamic Airspace

Autonomous Unmanned Aerial Vehicles (UAV) hold the potential to revolutionize logistics and transportation. To become truly viable, this technology must prove its capability to operate safely across a wide range of environments and conditions. Factors like wind, rain, hail, birds, and the presence of other drones in the airspace must all be considered in the decision-making process. While traditional control systems struggle with the complexity of this problem, machine learning has shown promise in tackling these challenges efficiently and effectively. This work proposes to advance independent drone operation through object avoidance, data collection, and smart navigation.