Project title:The fast and the furious: Artificial Intelligence-based autonomous pilots for drone racing
Project description: As intelligent robots become more prominent in the transport and entertainment industry, researchers go to great lengths to bring human-like maneuver skills to micro unmanned aerial vehicles. Drone racing is a great application for that problem, as it is a competitive sport in which autonomous drones race against each other, while also trying to beat professional pilots. Artificial intelligence, and more specifically computer vision, might be a game changer for this sector, where traditional rule-based approaches suffer from their rigidity. In this thesis, instead of dealing with perception-planning-control problems separately, a deep learning approach is used, where RGB images are used as input for a deep convolutional neural network, which outputs reference velocities for the drone on the x-, y-, z-axes. To keep track of the drone velocity at all times, visual-inertial odometry is utilized.