351 citations · 1.3k across the 22 of their papers we have counts for
3 papers · 2 filters
Beauty and the Beast: Optimal Methods Meet Learning for Drone Racing
Elia Kaufmann, Mathias Gehrig, Philipp Foehn +4
Autonomous micro aerial vehicles still struggle with fast and agile maneuvers, dynamic environments, imperfect sensing, and state estimation drift. Autonomous drone racing brings t…
Frequency-Aware Model Predictive Control
Ruben Grandia, Farbod Farshidian, Alexey Dosovitskiy +2
Transferring solutions found by trajectory optimization to robotic hardware remains a challenging task. When the optimization fully exploits the provided model to perform dynamic t…
Deep Drone Racing: Learning Agile Flight in Dynamic Environments
Elia Kaufmann, Antonio Loquercio, Rene Ranftl +3
Autonomous agile flight brings up fundamental challenges in robotics, such as coping with unreliable state estimation, reacting optimally to dynamically changing environments, and…