319 citations · 614 across the 14 of their papers we have counts for
4 papers · 1 filter
Safe Guaranteed Exploration for Non-linear Systems
Manish Prajapat, Johannes Köhler, Matteo Turchetta +2
Safely exploring environments with a-priori unknown constraints is a fundamental challenge that restricts the autonomy of robots. While safety is paramount, guarantees on sufficien…
Safe and Efficient Model-free Adaptive Control via Bayesian Optimization
Christopher König, Matteo Turchetta, John Lygeros +2
Adaptive control approaches yield high-performance controllers when a precise system model or suitable parametrizations of the controller are available. Existing data-driven approa…
Learning-based Model Predictive Control for Safe Exploration and Reinforcement Learning
Torsten Koller, Felix Berkenkamp, Matteo Turchetta +2
Reinforcement learning has been successfully used to solve difficult tasks in complex unknown environments. However, these methods typically do not provide any safety guarantees du…
Learning-based Model Predictive Control for Safe Exploration
Torsten Koller, Felix Berkenkamp, Matteo Turchetta +1
Learning-based methods have been successful in solving complex control tasks without significant prior knowledge about the system. However, these methods typically do not provide a…