Sebastian Trimpe

Pattern Recognit., March, 2024

On Safety in Safe Bayesian Optimization.

[BibT_eX]

[DOI]

CoRR, 2024

Learning Hybrid Dynamics Models with Simulator-Informed Latent States.

[BibT_eX]

[DOI]

Katharina Ensinger

Sebastian Ziesche

Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024

Exact Inference for Continuous-Time Gaussian Process Dynamics.

[BibT_eX]

[DOI]

Katharina Ensinger

Nicholas Tagliapietra

Sebastian Ziesche

Andres Felipe Posada-Moreno

Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024

2023

Scale-preserving automatic concept extraction (SPACE).

[BibT_eX]

[DOI]

Lukas Kreisköther

Tassilo Glander

Mach. Learn., November, 2023

GoSafeOpt: Scalable safe exploration for global optimization of dynamical systems.

[BibT_eX]

[DOI]

Artif. Intell., July, 2023

Safe Value Functions.

[BibT_eX]

[DOI]

Pierre-François Massiani

IEEE Trans. Autom. Control., May, 2023

Recognition Models to Learn Dynamics from Partial Observations with Neural ODEs.

[BibT_eX]

[DOI]

Trans. Mach. Learn. Res., 2023

Mean-Field Limits for Discrete-Time Dynamical Systems via Kernel Mean Embeddings.

[BibT_eX]

[DOI]

Michael Herty

IEEE Control. Syst. Lett., 2023

Automatic nonlinear MPC approximation with closed-loop guarantees.

[BibT_eX]

[DOI]

CoRR, 2023

Event-Triggered Safe Bayesian Optimization on Quadcopters.

[BibT_eX]

[DOI]

Antonia Holzapfel

Paul Brunzema

CoRR, 2023

Tracking Object Positions in Reinforcement Learning: A Metric for Keypoint Detection (extended version).

[BibT_eX]

[DOI]

Emma Cramer

Jonas Reiher

CoRR, 2023

On kernel-based statistical learning in the mean field limit.

[BibT_eX]

[DOI]

Michael Herty

CoRR, 2023

Finite element inspired networks: Learning physically-plausible deformable object dynamics from partial observations.

[BibT_eX]

[DOI]

CoRR, 2023

Experience Transfer for Robust Direct Data-Driven Control.

[BibT_eX]

[DOI]

Dmitrii Likhachev

CoRR, 2023

Approximate non-linear model predictive control with safety-augmented neural networks.

[BibT_eX]

[DOI]

CoRR, 2023

Multimodal Multi-User Surface Recognition with the Kernel Two-Sample Test.

[BibT_eX]

[DOI]

Behnam Khojasteh

Katherine J. Kuchenbecker

CoRR, 2023

Reproducing kernel Hilbert spaces in the mean field limit.

[BibT_eX]

[DOI]

CoRR, 2023

Data-Driven Observability Analysis for Nonlinear Stochastic Systems.

[BibT_eX]

[DOI]

Pierre-François Massiani

CoRR, 2023

Scalable Concept Extraction in Industry 4.0.

[BibT_eX]

[DOI]

Andres Felipe Posada-Moreno

Proceedings of the Explainable Artificial Intelligence, 2023

On kernel-based statistical learning theory in the mean field limit.

[BibT_eX]

[DOI]

Michael Herty

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Toward Multi-Agent Reinforcement Learning for Distributed Event-Triggered Control.

[BibT_eX]

[DOI]

Lukas Kesper

Proceedings of the Learning for Dynamics and Control Conference, 2023

Data-efficient Deep Reinforcement Learning for Vehicle Trajectory Control.

[BibT_eX]

[DOI]

Bernd Frauenknecht

Tobias Ehlgen

Proceedings of the 25th IEEE International Conference on Intelligent Transportation Systems, 2023

Combining Slow and Fast: Complementary Filtering for Dynamics Learning.

[BibT_eX]

[DOI]

Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence, 2023

2022

Identifying Causal Structure in Dynamical Systems.

[BibT_eX]

[DOI]

Karl Henrik Johansson

Trans. Mach. Learn. Res., 2022

Scaling beyond Bandwidth Limitations: Wireless Control with Stability Guarantees under Overload.

[BibT_eX]

[DOI]

ACM Trans. Cyber Phys. Syst., 2022

Learning Fast and Precise Pixel-to-Torque Control: A Platform for Reproducible Research of Learning on Hardware.

[BibT_eX]

[DOI]

Steffen Bleher

IEEE Robotics Autom. Mag., 2022

The Wheelbot: A Jumping Reaction Wheel Unicycle.

[BibT_eX]

[DOI]

IEEE Robotics Autom. Lett., 2022

Event-Triggered Time-Varying Bayesian Optimization.

[BibT_eX]

[DOI]

CoRR, 2022

Learning Fast and Precise Pixel-to-Torque Control.

[BibT_eX]

[DOI]

Steffen Bleher

CoRR, 2022

Event-triggered and distributed model predictive control for guaranteed collision avoidance in UAV swarms.

[BibT_eX]

[DOI]

Alexander Gräfe

Joram Eickhoff

CoRR, 2022

Learning dynamics from partial observations with structured neural ODEs.

[BibT_eX]

[DOI]

CoRR, 2022

Parameter Filter-based Event-triggered Learning.

[BibT_eX]

[DOI]

Sebastian Schlor

CoRR, 2022

Scalable Safe Exploration for Global Optimization of Dynamical Systems.

[BibT_eX]

[DOI]

CoRR, 2022

Structure-Preserving Gaussian Process Dynamics.

[BibT_eX]

[DOI]

Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2022

Revisiting the derivation of stage costs in infinite horizon discrete-time optimal control.

[BibT_eX]

[DOI]

Proceedings of the 30th Mediterranean Conference on Control and Automation, 2022

Improving the Performance of Robust Control through Event-Triggered Learning.

[BibT_eX]

[DOI]

Proceedings of the 61st IEEE Conference on Decision and Control, 2022

Towards remote fault detection by analyzing communication priorities.

[BibT_eX]

[DOI]

Alexander Gräfe

Proceedings of the 61st IEEE Conference on Decision and Control, 2022

Learning Functions and Uncertainty Sets Using Geometrically Constrained Kernel Regression.

[BibT_eX]

[DOI]

Proceedings of the 61st IEEE Conference on Decision and Control, 2022

On Controller Tuning with Time-Varying Bayesian Optimization.

[BibT_eX]

[DOI]

Paul Brunzema

Proceedings of the 61st IEEE Conference on Decision and Control, 2022

2021

Event-Triggered Learning for Linear Quadratic Control.

[BibT_eX]

[DOI]

Henning Schlüter

IEEE Trans. Autom. Control., 2021

Robot Learning With Crash Constraints.

[BibT_eX]

[DOI]

IEEE Robotics Autom. Lett., 2021

Wireless Control for Smart Manufacturing: Recent Approaches and Open Challenges.

[BibT_eX]

[DOI]

Proc. IEEE, 2021

Task space adaptation via the learning of gait controllers of magnetic soft millirobots.

[BibT_eX]

[DOI]

Int. J. Robotics Res., 2021

Learning event-triggered control from data through joint optimization.

[BibT_eX]

[DOI]

IFAC J. Syst. Control., 2021

Controller Design via Experimental Exploration With Robustness Guarantees.

[BibT_eX]

[DOI]

Tobias Holicki

IEEE Control. Syst. Lett., 2021

Joint State and Dynamics Estimation With High-Gain Observers and Gaussian Process Models.

[BibT_eX]

[DOI]

IEEE Control. Syst. Lett., 2021

Symplectic Gaussian Process Dynamics.

[BibT_eX]

[DOI]

CoRR, 2021

Learning by Doing: Controlling a Dynamical System using Causality, Control, and Reinforcement Learning.

[BibT_eX]

[DOI]

Sebastian Weichwald

Søren Wengel Mogensen

Proceedings of the NeurIPS 2021 Competitions and Demonstrations Track, 2021

Local policy search with Bayesian optimization.

[BibT_eX]

[DOI]

Sarah Müller

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Probabilistic robust linear quadratic regulators with Gaussian processes.

[BibT_eX]

[DOI]

Matthias Neumann-Brosig

Proceedings of the 3rd Annual Conference on Learning for Dynamics and Control, 2021

On exploration requirements for learning safety constraints.

[BibT_eX]

[DOI]

Pierre-François Massiani

Proceedings of the 3rd Annual Conference on Learning for Dynamics and Control, 2021

GoSafe: Globally Optimal Safe Robot Learning.

[BibT_eX]

[DOI]

Proceedings of the IEEE International Conference on Robotics and Automation, 2021

Using Physics Knowledge for Learning Rigid-body Forward Dynamics with Gaussian Process Force Priors.

[BibT_eX]

[DOI]

Lucas Rath

Andreas René Geist

Proceedings of the Conference on Robot Learning, 8-11 November 2021, London, UK., 2021

Learning-enhanced robust controller synthesis with rigorous statistical and control-theoretic guarantees.

[BibT_eX]

[DOI]

Proceedings of the 2021 60th IEEE Conference on Decision and Control (CDC), 2021

Practical and Rigorous Uncertainty Bounds for Gaussian Process Regression.

[BibT_eX]

[DOI]

Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, 2021

2020

Data-Efficient Autotuning With Bayesian Optimization: An Industrial Control Study.

[BibT_eX]

[DOI]

Matthias Neumann-Brosig

Alonso Marco

Dieter Schwarzmann

IEEE Trans. Control. Syst. Technol., 2020

Fast Feedback Control over Multi-hop Wireless Networks with Mode Changes and Stability Guarantees.

[BibT_eX]

[DOI]

ACM Trans. Cyber Phys. Syst., 2020

Overcoming Bandwidth Limitations in Wireless Sensor Networks by Exploitation of Cyclic Signal Patterns: An Event-triggered Learning Approach.

[BibT_eX]

[DOI]

Sensors, 2020

Safe and Fast Tracking on a Robot Manipulator: Robust MPC and Neural Network Control.

[BibT_eX]

[DOI]

IEEE Robotics Autom. Lett., 2020

Spatial Scheduling of Informative Meetings for Multi-Agent Persistent Coverage.

[BibT_eX]

[DOI]

Ravi N. Haksar

Mac Schwager

IEEE Robotics Autom. Lett., 2020

Sliding Mode Control with Gaussian Process Regression for Underwater Robots.

[BibT_eX]

[DOI]

Gabriel S. Lima

Wallace Moreira Bessa

J. Intell. Robotic Syst., 2020

Hierarchical Event-Triggered Learning for Cyclically Excited Systems With Application to Wireless Sensor Networks.

[BibT_eX]

[DOI]

IEEE Control. Syst. Lett., 2020

Control-Guided Communication: Efficient Resource Arbitration and Allocation in Multi-Hop Wireless Control Systems.

[BibT_eX]

[DOI]

IEEE Control. Syst. Lett., 2020

Structured learning of rigid-body dynamics: A survey and unified view.

[BibT_eX]

[DOI]

Andreas René Geist

CoRR, 2020

Excursion Search for Constrained Bayesian Optimization under a Limited Budget of Failures.

[BibT_eX]

[DOI]

Alonso Marco

José Miguel Hernández-Lobato

CoRR, 2020

A Kernel Two-sample Test for Dynamical Systems.

[BibT_eX]

[DOI]

CoRR, 2020

Event-triggered learning.

[BibT_eX]

[DOI]

Autom., 2020

Online learning with stability guarantees: A memory-based warm starting for real-time MPC.

[BibT_eX]

[DOI]

Autom., 2020

Learning of Sub-optimal Gait Controllers for Magnetic Walking Soft Millirobots.

[BibT_eX]

[DOI]

Proceedings of the Robotics: Science and Systems XVI, 2020

Learning Constrained Dynamics with Gauss' Principle adhering Gaussian Processes.

[BibT_eX]

[DOI]

Andreas Rene Geist

Proceedings of the 2nd Annual Conference on Learning for Dynamics and Control, 2020

Actively Learning Gaussian Process Dynamics.

[BibT_eX]

[DOI]

Mona Buisson-Fenet

Proceedings of the 2nd Annual Conference on Learning for Dynamics and Control, 2020

Robust Model-free Reinforcement Learning with Multi-objective Bayesian Optimization.

[BibT_eX]

[DOI]

Matteo Turchetta

Andreas Krause

Proceedings of the 2020 IEEE International Conference on Robotics and Automation, 2020

2019

Resource-Aware IoT Control: Saving Communication Through Predictive Triggering.

[BibT_eX]

[DOI]

IEEE Internet Things J., 2019

Safe and Fast Tracking Control on a Robot Manipulator: Robust MPC and Neural Network Control.

[BibT_eX]

[DOI]

CoRR, 2019

Predictive Triggering for Distributed Control of Resource Constrained Multi-agent Systems.

[BibT_eX]

[DOI]

José Mario Mastrangelo

CoRR, 2019

Classified Regression for Bayesian Optimization: Robot Learning with Unknown Penalties.

[BibT_eX]

[DOI]

CoRR, 2019

Demo Abstract: Fast Feedback Control and Coordination with Mode Changes for Wireless Cyber-Physical Systems.

[BibT_eX]

[DOI]

CoRR, 2019

Fast feedback control and coordination with mode changes for wireless cyber-physical systems: demo abstract.

[BibT_eX]

[DOI]

Proceedings of the 18th International Conference on Information Processing in Sensor Networks, 2019

Trajectory-Based Off-Policy Deep Reinforcement Learning.

[BibT_eX]

[DOI]

Proceedings of the 36th International Conference on Machine Learning, 2019

Feedback control goes wireless: guaranteed stability over low-power multi-hop networks.

[BibT_eX]

[DOI]

Proceedings of the 10th ACM/IEEE International Conference on Cyber-Physical Systems, 2019

Data-driven inference of passivity properties via Gaussian process optimization.

[BibT_eX]

[DOI]

Anne Romer

Frank Allgöwer

Proceedings of the 17th European Control Conference, 2019

A Learnable Safety Measure.

[BibT_eX]

[DOI]

Alexander Badri-Spröwitz

Proceedings of the 3rd Annual Conference on Robot Learning, 2019

Controlling Heterogeneous Stochastic Growth Processes on Lattices with Limited Resources.

[BibT_eX]

[DOI]

Proceedings of the 58th IEEE Conference on Decision and Control, 2019

Event-triggered Pulse Control with Model Learning (if Necessary).

[BibT_eX]

[DOI]

Karl Henrik Johansson

Proceedings of the 2019 American Control Conference, 2019

2018

Distributed Event-Based State Estimation for Networked Systems: An LMI Approach.

[BibT_eX]

[DOI]

Michael Muehlebach

IEEE Trans. Autom. Control., 2018

Learning an Approximate Model Predictive Controller With Guarantees.

[BibT_eX]

[DOI]

IEEE Control. Syst. Lett., 2018

Data-efficient Auto-tuning with Bayesian Optimization: An Industrial Control Study.

[BibT_eX]

[DOI]

Matthias Neumann-Brosig

Alonso Marco

Dieter Schwarzmann

CoRR, 2018

A Local Information Criterion for Dynamical Systems.

[BibT_eX]

[DOI]

CoRR, 2018

Minimum Information Exchange in Distributed Systems.

[BibT_eX]

[DOI]

CoRR, 2018

Depth Control of Underwater Robots Using Sliding Modes and Gaussian Process Regression.

[BibT_eX]

[DOI]

Gabriel S. Lima

Wallace Moreira Bessa

Proceedings of the Latin American Robotic Symposium, 2018

Gait Learning for Soft Microrobots Controlled by Light Fields.

[BibT_eX]

[DOI]

Proceedings of the 2018 IEEE/RSJ International Conference on Intelligent Robots and Systems, 2018

Toward fast closed-loop control over multi-hop low-power wireless networks: poster abstract.

[BibT_eX]

[DOI]

Proceedings of the 17th ACM/IEEE International Conference on Information Processing in Sensor Networks, 2018

Probabilistic Recurrent State-Space Models.

[BibT_eX]

[DOI]

Proceedings of the 35th International Conference on Machine Learning, 2018

Evaluating Low-Power Wireless Cyber-Physical Systems.

[BibT_eX]

[DOI]

Proceedings of the Workshop on Benchmarking Cyber-Physical Networks and Systems, 2018

Efficient Encoding of Dynamical Systems Through Local Approximations.

[BibT_eX]

[DOI]

Proceedings of the 57th IEEE Conference on Decision and Control, 2018

Deep Reinforcement Learning for Event-Triggered Control.

[BibT_eX]

[DOI]

Proceedings of the 57th IEEE Conference on Decision and Control, 2018

Event-Triggered Learning for Resource-Efficient Networked Control.

[BibT_eX]

[DOI]

Proceedings of the 2018 Annual American Control Conference, 2018

2017

Event-based State Estimation: An Emulation-based Approach.

[BibT_eX]

[DOI]

CoRR, 2017

Virtual vs. real: Trading off simulations and physical experiments in reinforcement learning with Bayesian optimization.

[BibT_eX]

[DOI]

Proceedings of the 2017 IEEE International Conference on Robotics and Automation, 2017

Model-based policy search for automatic tuning of multivariate PID controllers.

[BibT_eX]

[DOI]

Proceedings of the 2017 IEEE International Conference on Robotics and Automation, 2017

Optimizing Long-term Predictions for Model-based Policy Search.

[BibT_eX]

[DOI]

Proceedings of the 1st Annual Conference on Robot Learning, CoRL 2017, Mountain View, 2017

On the design of LQR kernels for efficient controller learning.

[BibT_eX]

[DOI]

Proceedings of the 56th IEEE Annual Conference on Decision and Control, 2017

2016

A new perspective and extension of the Gaussian Filter.

[BibT_eX]

[DOI]

Manuel Wüthrich

Daniel Kappler

Stefan Schaal

Int. J. Robotics Res., 2016

Communication rate analysis for event-based state estimation.

[BibT_eX]

[DOI]

Simon Ebner

Proceedings of the 13th International Workshop on Discrete Event Systems, 2016

Automatic LQR tuning based on Gaussian process global optimization.

[BibT_eX]

[DOI]

Proceedings of the 2016 IEEE International Conference on Robotics and Automation, 2016

Depth-based object tracking using a Robust Gaussian Filter.

[BibT_eX]

[DOI]

Jan Issac

Manuel Wüthrich

Jeannette Bohg

Stefan Schaal

Proceedings of the 2016 IEEE International Conference on Robotics and Automation, 2016

Predictive and self triggering for event-based state estimation.

[BibT_eX]

[DOI]

Proceedings of the 55th IEEE Conference on Decision and Control, 2016

Robust Gaussian filtering using a pseudo measurement.

[BibT_eX]

[DOI]

Manuel Wuthrich

Proceedings of the 2016 American Control Conference, 2016

2015

Robust Gaussian Filtering.

[BibT_eX]

[DOI]

Manuel Wüthrich

Stefan Schaal

CoRR, 2015

Distributed Event-based State Estimation.

[BibT_eX]

[DOI]

CoRR, 2015

A New Perspective and Extension of the Gaussian Filter.

[BibT_eX]

[DOI]

Proceedings of the Robotics: Science and Systems XI, Sapienza University of Rome, 2015

Event-based estimation and control for remote robot operation with reduced communication.

[BibT_eX]

[DOI]

Jonas Buchli

Proceedings of the IEEE International Conference on Robotics and Automation, 2015

On the choice of the event trigger in event-based estimation.

[BibT_eX]

[DOI]

Marco C. Campi

Proceedings of the International Conference on Event-based Control, 2015

Guaranteed ℋ2 performance in distributed event-based state estimation.

[BibT_eX]

[DOI]

Michael Muehlebach

Proceedings of the International Conference on Event-based Control, 2015

LMI-based synthesis for distributed event-based state estimation.

[BibT_eX]

[DOI]

Michael Muehlebach

Proceedings of the American Control Conference, 2015

2014

Event-Based State Estimation With Variance-Based Triggering.

[BibT_eX]

[DOI]

IEEE Trans. Autom. Control., 2014

A Limiting Property of the Matrix Exponential.

[BibT_eX]

[DOI]

IEEE Trans. Autom. Control., 2014

Stability analysis of distributed event-based state estimation.

[BibT_eX]

[DOI]

Proceedings of the 53rd IEEE Conference on Decision and Control, 2014

2011

Reduced communication state estimation for control of an unstable networked control system.

[BibT_eX]

[DOI]

Proceedings of the 50th IEEE Conference on Decision and Control and European Control Conference, 2011

2010

Accelerometer-based tilt estimation of a rigid body with only rotational degrees of freedom.

[BibT_eX]

[DOI]

Proceedings of the IEEE International Conference on Robotics and Automation, 2010

2009

A limiting property of the matrix exponential with application to multi-loop control.

[BibT_eX]

[DOI]

Proceedings of the 48th IEEE Conference on Decision and Control, 2009

2007

Less conservative polytopic LPV models for charge control by combining parameter set mapping and set intersection.

[BibT_eX]

[DOI]

Andreas Kwiatkowski