Lukas Hewing — accepted AI-conference papers

2022

Contextual Tuning of Model Predictive Control for Autonomous Racing

Lukas P. Fröhlich, Christian Küttel, Elena Arcari, Lukas Hewing, Melanie N. Zeilinger, Andrea Carron

IROS 2022poster

Learning-based model predictive control has been widely applied in autonomous racing to improve the closed-loop behaviour of vehicles in a data-driven manner. When environmental conditions change, e.g., due to rain, often only the predictive model is adapted, but the controller parameters are kept c…

Cited by 27 Source ↗Scholar ↗

2019

Data-Driven Model Predictive Control for Trajectory Tracking With a Robotic Arm

Andrea Carron, Elena Arcari, Martin Wermelinger, Lukas Hewing, Marco Hutter, Melanie N. Zeilinger

RA-L 2019

High-precision trajectory tracking is fundamental in robotic manipulation. While industrial robots address this through stiffness and high-performance hardware, compliant and cost-effective robots require advanced control to achieve accurate position tracking. In this letter, we present a model-base

Cited by 219 Source ↗Scholar ↗

2019

Learning-Based Model Predictive Control for Autonomous Racing

Juraj Kabzan, Lukas Hewing, Alexander Liniger, Melanie N. Zeilinger

RA-L 2019

In this letter, we present a learning-based control approach for autonomous racing with an application to the AMZ Driverless race car <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">gotthard</i> . One major issue in autonomous racing is that accurate

Cited by 425 Source ↗Scholar ↗