2 citations · 2 across the 4 of their papers we have counts for
7 papers · 1 filter
MonoRace: Winning Champion-Level Drone Racing with Robust Monocular AI
Stavrow A. Bahnam, Robin Ferede, Till M. Blaha +6
Autonomous drone racing represents a major frontier in robotics research. It requires an Artificial Intelligence (AI) that can run on board light-weight flying robots under tight r…
SkyDreamer: Interpretable End-to-End Vision-Based Drone Racing with Model-Based Reinforcement Learning
Aderik Verraest, Stavrow Bahnam, Robin Ferede +2
Autonomous drone racing (ADR) systems have recently achieved champion-level performance, yet remain highly specific to drone racing. While end-to-end vision-based methods promise b…
One Net to Rule Them All: Domain Randomization in Quadcopter Racing Across Different Platforms
Robin Ferede, Till Blaha, Erin Lucassen +2
In high-speed quadcopter racing, finding a single controller that works well across different platforms remains challenging. This work presents the first neural network controller…
End-to-end Reinforcement Learning for Time-Optimal Quadcopter Flight
Robin Ferede, Christophe De Wagter, Dario Izzo +1
Aggressive time-optimal control of quadcopters poses a significant challenge in the field of robotics. The state-of-the-art approach leverages reinforcement learning (RL) to train…
Optimality Principles in Spacecraft Neural Guidance and Control
Dario Izzo, Emmanuel Blazquez, Robin Ferede +3
Spacecraft and drones aimed at exploring our solar system are designed to operate in conditions where the smart use of onboard resources is vital to the success or failure of the m…
Guidance & Control Networks for Time-Optimal Quadcopter Flight
Sebastien Origer, Christophe De Wagter, Robin Ferede +2
Reaching fast and autonomous flight requires computationally efficient and robust algorithms. To this end, we train Guidance & Control Networks to approximate optimal control polic…