works on

From the 1 of 8 linked papers with an AI index.

collaborators

8 papers

cs.RO2026

WarpMPC: Large-Batch MPC on GPU via ADMM with Unrolled Factorization

Henrik Hose, Se Hwan Jeon, Charles Khazoom +2

The paper introduces WarpMPC, a GPU‑accelerated toolbox that speeds up large‑batch model predictive control by unrolling sparse LDLᵀ factorizations within an ADMM solver, achieving…

cs.LG2026

Uncertainty-Aware Predictive Safety Filters for Probabilistic Neural Network Dynamics

Bernd Frauenknecht, Lukas Kesper, Daniel Mayfrank +2

Predictive safety filters (PSFs) leverage model predictive control to enforce constraint satisfaction during deep reinforcement learning (RL) exploration, yet their reliance on fir…

cs.LG2026

Learning to Race in Minutes: Infoprop Dyna on the Mini Wheelbot

Devdutt Subhasish, Henrik Hose, Sebastian Trimpe

Reinforcement Learning (RL) has the potential to enable robots with fast, nonlinear, and unstable dynamics to reach the limits of their performance. However, most recent advances r…

cs.RO2026

The Mini Wheelbot Dataset: High-Fidelity Data for Robot Learning

Henrik Hose, Paul Brunzema, Devdutt Subhasish +1

The development of robust learning-based control algorithms for unstable systems requires high-quality, real-world data, yet access to specialized robotic hardware remains a signif…

cs.RO2026

Fine-Tuning of Neural Network Approximate MPC without Retraining via Bayesian Optimization

Henrik Hose, Paul Brunzema, Alexander von Rohr +3

Approximate model-predictive control (AMPC) aims to imitate an MPC's behavior with a neural network, removing the need to solve an expensive optimization problem at runtime. Howeve…

cs.RO2025

The Mini Wheelbot: A Testbed for Learning-based Balancing, Flips, and Articulated Driving

Henrik Hose, Jan Weisgerber, Sebastian Trimpe

The Mini Wheelbot is a balancing, reaction wheel unicycle robot designed as a testbed for learning-based control. It is an unstable system with highly nonlinear yaw dynamics, non-h…