7 papers
Safe and Non-Conservative Trajectory Planning for Autonomous Driving Handling Unanticipated Behaviors of Traffic Participants
Tommaso Benciolini, Michael Fink, Nehir Güzelkaya +2
Trajectory planning for autonomous driving is challenging because the unknown future motion of traffic participants must be accounted for, yielding large uncertainty. Stochastic Mo…
Minimal Constraint Violation Probability in Model Predictive Control for Linear Systems
Michael Fink, Tim Brüdigam, Dirk Wollherr +1
Handling uncertainty in model predictive control comes with various challenges, especially when considering state constraints under uncertainty. Most methods focus on either the co…
Combining Belief Function Theory and Stochastic Model Predictive Control for Multi-Modal Uncertainty in Autonomous Driving
Tommaso Benciolini, Yuntian Yan, Dirk Wollherr +1
In automated driving, predicting and accommodating the uncertain future motion of other traffic participants is challenging, especially in unstructured environments in which the hi…
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…