23 citations · 119 across the 20 of their papers we have counts for
6 papers · 1 filter
Active Exploration in Iterative Gaussian Process Regression for Uncertainty Modeling in Autonomous Racing
Tommaso Benciolini, Chen Tang, Marion Leibold +3
Autonomous racing creates challenging control problems, but Model Predictive Control (MPC) has made promising steps toward solving both the minimum lap-time problem and head-to-hea…
Incorporating Target Vehicle Trajectories Predicted by Deep Learning Into Model Predictive Controlled Vehicles
Ni Dang, Zengjie Zhang, Jizheng Liu +2
Model Predictive Control (MPC) has been widely applied to the motion planning of autonomous vehicles. An MPC-controlled vehicle is required to predict its own trajectories in a fin…
Optimal Control for Indoor Vertical Farms Based on Crop Growth
Annalena Daniels, Michael Fink, Marion Leibold +2
Vertical farming allows for year-round cultivation of a variety of crops, overcoming environmental limitations and ensuring food security. This closed and highly controlled system…
Identifying Reaction-Aware Driving Styles of Stochastic Model Predictive Controlled Vehicles by Inverse Reinforcement Learning
Ni Dang, Tao Shi, Zengjie Zhang +3
The driving style of an Autonomous Vehicle (AV) refers to how it behaves and interacts with other AVs. In a multi-vehicle autonomous driving system, an AV capable of identifying th…
An Online Adaptation Strategy for Direct Data-driven Control
Johannes Teutsch, Sebastian Ellmaier, Sebastian Kerz +2
The fundamental lemma from behavioral systems theory yields a data-driven non-parametric system representation that has shown great potential for the data-efficient control of unkn…
Offline Uncertainty Sampling in Data-driven Stochastic MPC
Johannes Teutsch, Sebastian Kerz, Tim Brüdigam +2
In this work, we exploit an offline-sampling based strategy for the constrained data-driven predictive control of an unknown linear system subject to random measurement noise. The…