35 citations · 180 across the 39 of their papers we have counts for
41 papers
Preconditioning for Diffuse Interface Tumor Growth Models
Jessica Bosch, Pelin Çiloğlu, Chen Greif +1
Computational models of tumor growth form a contemporary area of study. Diffuse interface models have been proposed as an important tool for cancer modeling. In this work, we consi…
Stabilize-then-optimize: Feedback transformations as preconditioners in optimal control
Till Preuster, Manuel Schaller, Anton Schiela +1
Many numerical algorithms for optimal control leverage an elimination of the state via the control-to-state map such as condensed approaches or preconditioned conjugate gradient me…
The Integration of Prediction and Planning in Deep Learning Automated Driving Systems: A Review
Steffen Hagedorn, Marcel Hallgarten, Martin Stoll +1
Automated driving has the potential to revolutionize personal, public, and freight mobility. Beside accurately perceiving the environment, automated vehicles must plan a safe, comf…
Uncertainty Propagation of Initial Conditions in Thermal Models
Alexandra Bünger, Roland Herzog, Andreas Naumann +1
The operation of machine tools often demands a highly accurate knowledge of the tool center point's (TCP) position. The displacement of the TCP over time can be inferred from therm…
Stay on Track: A Frenet Wrapper to Overcome Off-road Trajectories in Vehicle Motion Prediction
Marcel Hallgarten, Ismail Kisa, Martin Stoll +1
Predicting the future motion of observed vehicles is a crucial enabler for safe autonomous driving. The field of motion prediction has seen large progress recently with state-of-th…
Scaling Planning for Automated Driving using Simplistic Synthetic Data
Martin Stoll, Markus Mazzola, Maxim Dolgov +2
We challenge the perceived consensus that the application of deep learning to solve the automated driving planning task necessarily requires huge amounts of real-world data or high…