351 citations · 1.5k across the 18 of their papers we have counts for
22 papers
Agilicious: Open-Source and Open-Hardware Agile Quadrotor for Vision-Based Flight
Philipp Foehn, Elia Kaufmann, Angel Romero +8
Autonomous, agile quadrotor flight raises fundamental challenges for robotics research in terms of perception, planning, learning, and control. A versatile and standardized platfor…
Learning Agile, Vision-based Drone Flight: from Simulation to Reality
Davide Scaramuzza, Elia Kaufmann
We present our latest research in learning deep sensorimotor policies for agile, vision-based quadrotor flight. We show methodologies for the successful transfer of such policies f…
Autonomous Drone Racing: A Survey
Drew Hanover, Antonio Loquercio, Leonard Bauersfeld +6
Over the last decade, the use of autonomous drone systems for surveying, search and rescue, or last-mile delivery has increased exponentially. With the rise of these applications c…
User-Conditioned Neural Control Policies for Mobile Robotics
Leonard Bauersfeld, Elia Kaufmann, Davide Scaramuzza
Recently, learning-based controllers have been shown to push mobile robotic systems to their limits and provide the robustness needed for many real-world applications. However, onl…
Learned Inertial Odometry for Autonomous Drone Racing
Giovanni Cioffi, Leonard Bauersfeld, Elia Kaufmann +1
Inertial odometry is an attractive solution to the problem of state estimation for agile quadrotor flight. It is inexpensive, lightweight, and it is not affected by perceptual degr…
Learning Minimum-Time Flight in Cluttered Environments
Robert Penicka, Yunlong Song, Elia Kaufmann +1
We tackle the problem of minimum-time flight for a quadrotor through a sequence of waypoints in the presence of obstacles while exploiting the full quadrotor dynamics. Early works…
Real-time Neural-MPC: Deep Learning Model Predictive Control for Quadrotors and Agile Robotic Platforms
Tim Salzmann, Elia Kaufmann, Jon Arrizabalaga +3
Model Predictive Control (MPC) has become a popular framework in embedded control for high-performance autonomous systems. However, to achieve good control performance using MPC, a…
A Benchmark Comparison of Learned Control Policies for Agile Quadrotor Flight
Elia Kaufmann, Leonard Bauersfeld, Davide Scaramuzza
Quadrotors are highly nonlinear dynamical systems that require carefully tuned controllers to be pushed to their physical limits. Recently, learning-based control policies have bee…
Learning High-Speed Flight in the Wild
Antonio Loquercio, Elia Kaufmann, René Ranftl +3
Quadrotors are agile. Unlike most other machines, they can traverse extremely complex environments at high speeds. To date, only expert human pilots have been able to fully exploit…
Performance, Precision, and Payloads: Adaptive Nonlinear MPC for Quadrotors
Drew Hanover, Philipp Foehn, Sihao Sun +2
Agile quadrotor flight in challenging environments has the potential to revolutionize shipping, transportation, and search and rescue applications. Nonlinear model predictive contr…
A Comparative Study of Nonlinear MPC and Differential-Flatness-Based Control for Quadrotor Agile Flight
Sihao Sun, Angel Romero, Philipp Foehn +2
Accurate trajectory tracking control for quadrotors is essential for safe navigation in cluttered environments. However, this is challenging in agile flights due to nonlinear dynam…
NeuroBEM: Hybrid Aerodynamic Quadrotor Model
Leonard Bauersfeld, Elia Kaufmann, Philipp Foehn +2
Quadrotors are extremely agile, so much in fact, that classic first-principle-models come to their limits. Aerodynamic effects, while insignificant at low speeds, become the domina…
Data-Driven MPC for Quadrotors
Guillem Torrente, Elia Kaufmann, Philipp Foehn +1
Aerodynamic forces render accurate high-speed trajectory tracking with quadrotors extremely challenging. These complex aerodynamic effects become a significant disturbance at high…
Autonomous Overtaking in Gran Turismo Sport Using Curriculum Reinforcement Learning
Yunlong Song, HaoChih Lin, Elia Kaufmann +2
Professional race-car drivers can execute extreme overtaking maneuvers. However, existing algorithms for autonomous overtaking either rely on simplified assumptions about the vehic…
Autonomous Drone Racing with Deep Reinforcement Learning
Yunlong Song, Mats Steinweg, Elia Kaufmann +1
In many robotic tasks, such as autonomous drone racing, the goal is to travel through a set of waypoints as fast as possible. A key challenge for this task is planning the time-opt…
Flightmare: A Flexible Quadrotor Simulator
Yunlong Song, Selim Naji, Elia Kaufmann +2
State-of-the-art quadrotor simulators have a rigid and highly-specialized structure: either are they really fast, physically accurate, or photo-realistic. In this work, we propose…
Super-Human Performance in Gran Turismo Sport Using Deep Reinforcement Learning
Florian Fuchs, Yunlong Song, Elia Kaufmann +2
Autonomous car racing is a major challenge in robotics. It raises fundamental problems for classical approaches such as planning minimum-time trajectories under uncertain dynamics…
Deep Drone Acrobatics
Elia Kaufmann, Antonio Loquercio, René Ranftl +3
Performing acrobatic maneuvers with quadrotors is extremely challenging. Acrobatic flight requires high thrust and extreme angular accelerations that push the platform to its physi…
AlphaPilot: Autonomous Drone Racing
Philipp Foehn, Dario Brescianini, Elia Kaufmann +4
This paper presents a novel system for autonomous, vision-based drone racing combining learned data abstraction, nonlinear filtering, and time-optimal trajectory planning. The syst…
Deep Drone Racing: From Simulation to Reality with Domain Randomization
Antonio Loquercio, Elia Kaufmann, René Ranftl +3
Dynamically changing environments, unreliable state estimation, and operation under severe resource constraints are fundamental challenges that limit the deployment of small autono…
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…
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…