23 citations · 119 across the 20 of their papers we have counts for
5 papers · 1 filter
Data Generation Method for Learning a Low-dimensional Safe Region in Safe Reinforcement Learning
Zhehua Zhou, Ozgur S. Oguz, Yi Ren +2
Safe reinforcement learning aims to learn a control policy while ensuring that neither the system nor the environment gets damaged during the learning process. For implementing saf…
Model Predictive Control with Models of Different Granularity and a Non-uniformly Spaced Prediction Horizon
Tim Brüdigam, Daniel Prader, Dirk Wollherr +1
Horizon length and model accuracy are defining factors when designing a Model Predictive Controller. While long horizons and detailed models have a positive effect on control perfo…
Multistage Stochastic Model Predictive Control for Urban Automated Driving
Tommaso Benciolini, Tim Brüdigam, Marion Leibold
Trajectory planning in urban automated driving is challenging because of the high uncertainty resulting from the unknown future motion of other traffic participants. Robust approac…
Collision Avoidance with Stochastic Model Predictive Control for Systems with a Twofold Uncertainty Structure
Tim Brüdigam, Jie Zhan, Dirk Wollherr +1
Model Predictive Control (MPC) has shown to be a successful method for many applications that require control. Especially in the presence of prediction uncertainty, various types o…
Gaussian Process-based Stochastic Model Predictive Control for Overtaking in Autonomous Racing
Tim Brüdigam, Alexandre Capone, Sandra Hirche +2
A fundamental aspect of racing is overtaking other race cars. Whereas previous research on autonomous racing has majorly focused on lap-time optimization, here, we propose a method…