Deep Drone Racing: From Simulation to Reality with Domain Randomization

Dynamically changing environments, unreliable state estimation, and operation under severe resource constraints are fundamental challenges for robotics, which still limit the deployment of small autonomous drones. We address these challenges in the... Read more »

Are We Ready for Autonomous Drone Racing? The UZH-FPV Drone Racing Dataset

(NB. This video is narrated). Despite impressive results in visual-inertial state estimation in recent years, high speed trajectories with six degree of freedom motion remain challenging for existing estimation algorithms. Aggressive trajectories... Read more »

IROS 2018 Autonomous Drone Race: Optimal Methods meet Deep Learning for Autonomous Drone Racing

This video shows our team performance at the 3rd edition of the international IROS 2018 Autonomous Drone Racing Competition, which took place during the IROS 2018 conference in Madrid on October 3,... Read more »