Jonas Umlauft
Title
Cited by
Cited by
Year
Feedback linearization using Gaussian processes
J Umlauft, T Beckers, M Kimmel, S Hirche
2017 IEEE 56th Annual Conference on Decision and Control (CDC), 5249-5255, 2017
362017
An uncertainty-based control Lyapunov approach for control-affine systems modeled by Gaussian process
J Umlauft, L Pöhler, S Hirche
IEEE Control Systems Letters 2 (3), 483-488, 2018
342018
Uniform error bounds for Gaussian process regression with application to safe control
A Lederer, J Umlauft, S Hirche
arXiv preprint arXiv:1906.01376, 2019
332019
Feedback linearization based on Gaussian processes with event-triggered online learning
J Umlauft, S Hirche
IEEE Transactions on Automatic Control 65 (10), 4154-4169, 2019
222019
Dynamic movement primitives for cooperative manipulation and synchronized motions
J Umlauft, D Sieber, S Hirche
2014 IEEE International Conference on Robotics and Automation (ICRA), 766-771, 2014
222014
Scenario-based optimal control for Gaussian process state space models
J Umlauft, T Beckers, S Hirche
2018 European Control Conference (ECC), 1386-1392, 2018
202018
Stable model-based control with Gaussian process regression for robot manipulators
T Beckers, J Umlauft, S Hirche
IFAC-PapersOnLine 50 (1), 3877-3884, 2017
202017
Stable Gaussian process based tracking control of Lagrangian systems
T Beckers, J Umlauft, D Kulic, S Hirche
2017 IEEE 56th Annual Conference on Decision and Control (CDC), 5180-5185, 2017
182017
Learning Stable Gaussian Process State Space Models
J Umlauft, A Lederer, S Hirche
2017 American Control Conference (ACC) 1, 6428-6434, 2017
182017
Mean square prediction error of misspecified Gaussian process models
T Beckers, J Umlauft, S Hirche
2018 IEEE Conference on Decision and Control (CDC), 1162-1167, 2018
152018
Gaussian processes for dynamic movement primitives with application in knowledge-based cooperation
Y Fanger, J Umlauft, S Hirche
2016 IEEE/RSJ International Conference on Intelligent Robots and Systems …, 2016
132016
Bayesian Uncertainty Modeling for Programming by Demonstration
J Umlauft, Y Fanger, S Hirche
2017 IEEE International Conference on Robotics and Automation (ICRA) 1, 6428 …, 2017
122017
Learning stable stochastic nonlinear dynamical systems
J Umlauft, S Hirche
International Conference on Machine Learning, 3502-3510, 2017
92017
Posterior variance analysis of Gaussian processes with application to average learning curves
A Lederer, J Umlauft, S Hirche
arXiv preprint arXiv:1906.01404, 2019
82019
Localized active learning of Gaussian process state space models
A Capone, G Noske, J Umlauft, T Beckers, A Lederer, S Hirche
Learning for Dynamics and Control, 490-499, 2020
72020
Learning stochastically stable Gaussian process state–space models
J Umlauft, S Hirche
IFAC Journal of Systems and Control 12, 100079, 2020
52020
Smart forgetting for safe online learning with Gaussian processes
J Umlauft, T Beckers, A Capone, A Lederer, S Hirche
Learning for Dynamics and Control, 160-169, 2020
42020
How training data impacts performance in learning-based control
A Lederer, A Capone, J Umlauft, S Hirche
IEEE Control Systems Letters 5 (3), 905-910, 2020
42020
Data selection for multi-task learning under dynamic constraints
A Capone, A Lederer, J Umlauft, S Hirche
IEEE Control Systems Letters 5 (3), 959-964, 2020
22020
Uncertainty-based human motion tracking with stable Gaussian process state space models
L Pöhler, J Umlauft, S Hirche
IFAC-PapersOnLine 51 (34), 8-14, 2019
22019
The system can't perform the operation now. Try again later.
Articles 1–20