351 citations · 1.5k across the 18 of their papers we have counts for
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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…