4 citations · 5 across the 6 of their papers we have counts for
3 papers · 1 filter
Exploiting Hierarchical Controller Structure in Contextual Parameter Learning for Humanoid Loco-Manipulation
Sebastian Hirt, Lukas Theiner, Jan Peters +1
Hierarchical control architectures are widely used to decompose complex control problems into interacting control levels and are particularly important in robotics, where planning,…
Real-time Gaussian Process based Approximate Model Predictive Trajectory Tracking Control for Autonomous Vehicles
Alexander Rose, Lukas Theiner, Rolf Findeisen
Applying model predictive control on embedded systems remains challenging due to the high computational cost of solving optimal control problems. To address this limitation, comput…
Efficient Controller Learning from Human Preferences and Numerical Data Via Multi-Modal Surrogate Models
Lukas Theiner, Maik Pfefferkorn, Yongpeng Zhao +2
Tuning control policies manually to meet high-level objectives is often time-consuming. Bayesian optimization provides a data-efficient framework for automating this process using…