GoSafe: Globally Optimal Safe Robot Learning

GoSafe: Globally Optimal Safe Robot Learning

27 May 2021

Dominik Baumann

Sebastian Trimpe

Papers citing "GoSafe: Globally Optimal Safe Robot Learning"

11 / 11 papers shown

Title
Safety and optimality in learning-based control at low computational cost Dominik Baumann Krzysztof Kowalczyk Cristian R. Rojas K. Tiels Pawel Wachel 34 0 0 12 May 2025
Local Bayesian Optimization for Controller Tuning with Crash Constraints Alexander von Rohr David Stenger Dominik Scheurenberg Sebastian Trimpe 83 1 0 25 Nov 2024
Towards safe Bayesian optimization with Wiener kernel regression O. Molodchyk Johannes Teutsch T. Faulwasser 31 0 0 04 Nov 2024
ActSafe: Active Exploration with Safety Constraints for Reinforcement Learning Yarden As Bhavya Sukhija Lenart Treven Carmelo Sferrazza Stelian Coros Andreas Krause 38 1 0 12 Oct 2024
PACSBO: Probably approximately correct safe Bayesian optimization Abdullah Tokmak Thomas B. Schon Dominik Baumann 37 2 0 02 Sep 2024
Future Aware Safe Active Learning of Time Varying Systems using Gaussian Processes Markus Lange-Hegermann Christoph Zimmer AI4TS 47 0 0 17 May 2024
Global Safe Sequential Learning via Efficient Knowledge Transfer Cen-You Li Olaf Duennbier Marc Toussaint Barbara Rakitsch Christoph Zimmer 52 2 0 22 Feb 2024
Machine Learning Meets Advanced Robotic Manipulation Saeid Nahavandi R. Alizadehsani D. Nahavandi Chee Peng Lim Kevin Kelly Fernando Bello 29 17 0 22 Sep 2023
Bayesian inference for data-efficient, explainable, and safe robotic motion planning: A review Chengmin Zhou Chao Wang Haseeb Hassan H. Shah Bingding Huang Pasi Fränti 3DV 43 3 0 16 Jul 2023
A Human-Centered Safe Robot Reinforcement Learning Framework with Interactive Behaviors Shangding Gu Alap Kshirsagar Yali Du Guang Chen Jan Peters Alois C. Knoll 39 14 0 25 Feb 2023
GoSafeOpt: Scalable Safe Exploration for Global Optimization of Dynamical Systems Bhavya Sukhija M. Turchetta David Lindner Andreas Krause Sebastian Trimpe Dominik Baumann 36 17 0 24 Jan 2022