H2020 ERC Consolidator CO-MAN

CO-MAN: Safe data-driven control for human-centric systems

The research project CO-MAN aims to develop a novel framework for user-adaptive data-driven control with performance guarantees in order to address the scientific challenges of high uncertainty and individual user requirements.

Motivation

It is important for advances in technology to support human activities and interactions in the areas of healthcare, mobility and infrastructure systems. For instance, making healthcare more human requires digital interfaces to allow for more human interactions with the system. This is the goal of human-centric systems in which the human is both an element of the control system and a design criterion. The EU-funded CO-MAN project will develop a framework for user-adaptive data-driven control with performance guarantees. The biggest challenge will be to merge probabilistic non-parametric modelling techniques from statistical learning theory with novel risk-aware control methodologies while including active user modelling. The game changer is the current push towards reliable machine learning with novel results on theoretical bounds for learning behaviour.

Research topics

Links

TUM team members

Sandra Hirche (principal investigator)
Satoshi Endo
Alexandre Capone
Neha Das
Giulio Evangelisti
Armin Lederer
Hossein Kaviani rad
Hatem Sultan (project manager)

2024

Capone, Alexandre; Brüdigam, Tim; Hirche, Sandra: Online Constraint Tightening in Stochastic Model Predictive Control: A Regression Approach. IEEE Transactions on Automatic Control, 2024, 1-15 mehr… BibTeX Volltext ( DOI ) Volltext (mediaTUM)
Evangelisti, Giulio; Hirche, Sandra: Data-Driven Momentum Observers With Physically Consistent Gaussian Processes. IEEE Transactions on Robotics 40, 2024, 1938-1951 mehr… BibTeX Volltext ( DOI ) Volltext (mediaTUM)
Lefringhausen, Robert; Srithasan, Supitsana; Lederer, Armin; Hirche, Sandra: Learning-Based Optimal Control with Performance Guarantees for Unknown Systems with Latent States. 2024 European Control Conference (ECC), 2024, 90-97 mehr… BibTeX Volltext ( DOI ) Volltext (mediaTUM)

2023

A. Lederer; A. Begzadi; N. Das; S. Hirche: Safe Learning-Based Control of Elastic Joint Robots via Control Barrier Functions. 2023, The 22nd World Congress of the International Federation of Automatic Control, 2023 mehr… BibTeX Volltext (mediaTUM)
Armin Lederer; Erfaun Noorani; John S. Baras; Sandra Hirche: Risk-Sensitive Inhibitory Control for Safe Reinforcement Learning. IEEE Conference on Decision and Control, 2023, 1040-1045 mehr… BibTeX Volltext (mediaTUM)
Das, Neha; Endo, Satoshi; Patel, Sabrina; Krewer, Carmen; Hirche, Sandra: Online detection of compensatory strategies in human movement with supervised classification: a pilot study. Frontiers in Neurorobotics 17, 2023 mehr… BibTeX Volltext ( DOI )
H. Kavianirad; M. Forouhar; H. Sadeghian; S. Endo; S. Haddadin; S. Hirche: Model-Based Shared Control of a Hybrid FES-Exoskeleton: an Application in Participant-Specific Robotic Rehabilitation. 2023 International Conference on Rehabilitation Robotics, ICORR 2023, 2023 mehr… BibTeX Volltext ( DOI ) Volltext (mediaTUM)
Li, Cong; Liu, Qingchen; Qin, Jiahu; Buss, Martin; Hirche, Sandra: Safe Planning and Control Under Uncertainty: A Model-Free Design With One-Step Backward Data. IEEE Transactions on Industrial Electronics 71 (1), 2023, 729-738 mehr… BibTeX Volltext ( DOI ) Volltext (mediaTUM)
Li, Jiacheng; Liu, Qingchen; Jin, Wanxin; Qin, Jiahu; Hirche, Sandra: Robust Safe Learning and Control in an Unknown Environment: An Uncertainty-Separated Control Barrier Function Approach. IEEE Robotics and Automation Letters 8 (10), 2023, 6539-6546 mehr… BibTeX Volltext ( DOI )
N. Das; J. Umlauft; A. Lederer; A. Capone; T. Beckers; S. Hirche: Deep Learning based Uncertainty Decomposition for Real-time Control. 2023, The 22nd World Congress of the International Federation of Automatic Control, 2023 mehr… BibTeX Volltext (mediaTUM)
Omainska, Marco; Yamauchi, Junya; Lederer, Armin; Hirche, Sandra; Fujita, Masayuki: Rigid Motion Gaussian Processes With SE(3) Kernel and Application to Visual Pursuit Control. IEEE Control Systems Letters 7, 2023, 2665-2670 mehr… BibTeX Volltext ( DOI ) Volltext (mediaTUM)
Römer, Ralf; Lederer, Armin; Tesfazgi, Samuel; Hirche, Sandra: Vision-Based Uncertainty-Aware Motion Planning Based on Probabilistic Semantic Segmentation. IEEE Robotics and Automation Letters 8 (11), 2023, 7825-7832 mehr… BibTeX Volltext ( DOI ) Volltext (mediaTUM)

2022

A. Capone; A. Lederer; S. Hirche: Gaussian Process Uniform Error Bounds with Unknown Hyperparameters for Safety-Critical Applications. Proceedings of the 39th International Conference on Machine Learning, 2022 mehr… BibTeX Volltext (mediaTUM)
A. J. Ordóñez-Conejo; A. Lederer; S. Hirche: Adaptive Low-Pass Filtering using Sliding Window Gaussian Processes. Proceedings of the European Control Conference, 2022, 2234-2240 mehr… BibTeX Volltext ( DOI ) Volltext (mediaTUM)
A. Lederer; M. Zhang; S. Tesfazgi; S. Hirche: Networked Online Learning for Control of Safety-Critical Resource-Constrained Systems based on Gaussian Processes. Proceedings of the IEEE Conference on Control Technology and Applications, 2022 mehr… BibTeX Volltext (mediaTUM)
A. Lederer; Z. Yang; J. Jiao; S. Hirche: Cooperative Control of Uncertain Multi-Agent Systems via Distributed Gaussian Processes. IEEE Transactions on Automatic Control, 2022 mehr… BibTeX Volltext (mediaTUM)
G. Evangelisti; S. Hirche: Physically Consistent Learning of Conservative Lagrangian Systems with Gaussian Processes. 2022 IEEE 61st Conference on Decision and Control (CDC), IEEE, 2022 mehr… BibTeX Volltext ( DOI ) Volltext (mediaTUM)
H. Kavianirad; S. Endo; T. Keller; S. Hirche: EMG-Based Volitional Torque Estimation in Functional Electrical Stimulation Control. 2022 IEEE-EMBS Conference on Biomedical Engineering and Sciences (IECBES), 2022 mehr… BibTeX Volltext (mediaTUM)
Jiao, Junjie; Capone, Alexandre; Hirche, Sandra: Backstepping tracking control using Gaussian processes with event-triggered online learning. IEEE Control Systems Letters, 2022, 3176 - 3181 mehr… BibTeX Volltext (mediaTUM)
S. Curi; A. Lederer; S. Hirche; A. Krause: Safe Reinforcement Learning via Confidence-Based Filters. Proceedings of the IEEE Conference on Decision and Control, 2022 mehr… BibTeX Volltext (mediaTUM)
T. Beckers; Leonardo J. Colombo; S. Hirche: SAFE TRAJECTORY TRACKING FOR UNDERACTUATED VEHICLES WITH PARTIALLY UNKNOWN DYNAMICS. AIMS Journal, 2022 mehr… BibTeX Volltext (mediaTUM)
T. Beckers; S. Hirche: Prediction with Approximated Gaussian Process Dynamical Models. IEEE Transactions on Automatic Control (TAC) 2022, 2022 mehr… BibTeX Volltext ( DOI ) Volltext (mediaTUM)

2021

A. Lederer; A. J. Ordóñez Conejo; K. Maier; W. Xiao; J. Umlauft; S. Hirche: Gaussian Process-Based Real-Time Learning for Safety Critical Applications. Proceedings of the 38th International Conference on Machine Learning (Proceedings of Machine Learning Research 139), 2021, 6055-6064 mehr… BibTeX Volltext (mediaTUM)
Degue, Kwassi H.; Efimov, Denis; Le Ny, Jerome; Hirche, Sandra: Design of Interval Observers for Uncertain Linear Impulsive Systems. 2021 60th IEEE Conference on Decision and Control (CDC), IEEE, 2021 mehr… BibTeX Volltext ( DOI ) Volltext (mediaTUM)
K. H. Degue; D. Efimov; J. Le Ny; S. Hirche: Novel_Interval_Observer_Hybrid_Systems_Final_Version. 2021 60th IEEE Conference on Decision and Control, 2021 mehr… BibTeX Volltext (mediaTUM)
M. Omainska; J. Yamauchi; T. Beckers; T. Hatanaka; S. Hirche; M. Fujita: Gaussian process-based visual pursuit control with unknown target motion learning in three dimensions. SICE Journal of Control, Measurement, and System Integration 14 (1), 2021, 116-127 mehr… BibTeX Volltext ( DOI )
T. Beckers; S. Hirche: Prediction with Approximated Gaussian Process Dynamical Models. IEEE Transactions on Automatic Control , 2021 mehr… BibTeX Volltext ( DOI )
Yamauchi, Junya; Omainska, Marco; Beckers, Thomas; Hatanaka, Takeshi; Hirche, Sandra; Fujita, Masayuki: Cooperative Visual Pursuit Control with Learning of Position Dependent Target Motion via Gaussian Process. 2021 60th IEEE Conference on Decision and Control (CDC), IEEE, 2021 mehr… BibTeX Volltext ( DOI )

2020

A. Capone; G.Noske; J. Umlauft; T. Beckers; A. Lederer; S. Hirche: Localized active learning of Gaussian process state space models. Learning for Dynamics & Control, 2020 mehr… BibTeX Volltext (mediaTUM)
A. Capone; A. Lederer; J. Umlauft; S. Hirche: Data Selection for Multi-Task Learning Under Dynamic Constraints. IEEE Control Systems Letters 5 (3), 2020, 959-964 mehr… BibTeX Volltext ( DOI ) Volltext (mediaTUM)
A. Lederer; A. Capone; J. Umlauft; S. Hirche: How Training Data Impacts Performance in Learning-based Control. IEEE Control Systems Letters 5 (3), 2020, 905-910 mehr… BibTeX Volltext ( DOI ) Volltext (mediaTUM)
J. Umlauft; T. Beckers; A. Capone; A. Lederer; S. Hirche: Smart Forgetting for Safe Online Learning with Gaussian Processes. Learning for Dynamics & Control, 2020 mehr… BibTeX Volltext (mediaTUM)
Pfister, Franz M. J.; Um, Terry Taewoong; Pichler, Daniel C.; Goschenhofer, Jann; Abedinpour, Kian; Lang, Muriel; Endo, Satoshi; Ceballos-Baumann, Andres O.; Hirche, Sandra; Bischl, Bernd; Kulić, Dana; Fietzek, Urban M.: High-Resolution Motor State Detection in Parkinson's Disease Using Convolutional Neural Networks. Scientific Reports 10 (1), 2020, 5860 mehr… BibTeX Volltext ( DOI ) Volltext (mediaTUM)