Publications

Under review

T. Beckers, L. Colombo, M. Morari, and G. Pappas. Online Learning-based Balancing of Feed-forward and Feedback Control”. 2021.

T. Beckers, L. Colombo, and S. Hirche. Safe Trajectory Tracking for Underactuated Vehicles with Partially Unknown Dynamics”. 2021.

J. Umlauft, A. Lederer, T. Beckers, and S. Hirche. “Real-time Uncertainty Decomposition for Online Learning Control”.
arXiv: 2010.02613 [cs.LG]. 2020. [Preprint]

T. Beckers and S. Hirche. Prediction with Approximated Gaussian Process Dynamical Models”.
arXiv: 2006.14551 [eess.SY]. 2020. [Preprint] [bibtex]


Peer-reviewed articles

T. Beckers, S. Hirche, and L. Colombo. Safe Online Learning-based Formation Control of Multi-Agent Systems with Gaussian Processes”.
In: Proceedings of the Conference on Decision and Control (accepted). 2021. [Preprint] [Video]

J. Yamauchi, M. Omainska, T. Beckers, T. Hatanaka, S. Hirche, M. Fujita. “Cooperative Visual Pursuit Control with Learning of Position Dependent Target Motion via Gaussian Process”. In: Proceedings of the Conference on Decision and Control (accepted). 2021.

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”.
In: SICE Journal of Control, Measurement, and System Integration. 2021. doi: 10.1080/18824889.2021.1936855

A. Lederer, A. Capone, T. Beckers, J. Umlauft, and S. Hirche. “The Value of Data in Learning-based Control for Training Subset Selection”.
In: Proceedings of the 3rd Conference on Learning for Dynamics and Control. 2021. [Preprint] [bibtex]

J. Yamauchi, T. Beckers, M. Omainska, T. Hatanaka, S. Hirche, M. Fujita. “Visual Pursuit Control with Target Motion Learning via Gaussian Process”.
In: Proceedings of the Conference of the Society of Instrument and Control Engineers of Japan. 2020. doi: 10.23919/SICE48898.2020.9240221. [bibtex]
(Finalist of SICE Annual Conference International Award)

J. Umlauft, T. Beckers, A. Capone, A. Lederer, and S. Hirche. “Smart Forgetting for Safe Online Learning with Gaussian Processes”.
In: Proceedings of the 2nd Conference on Learning for Dynamics and Control. 2020. [Preprint] [bibtex] [Video]

A. Capone, G. Noske, J. Umlauft, T. Beckers, A. Lederer, and S. Hirche. “Localized Active Learning of Gaussian Process State Space Models”.
In: Proceedings of the 2nd Conference on Learning for Dynamics and Control. 2020. [Preprint] [bibtex] [Video]

T. Beckers, D. Kulić, and S. Hirche. “Stable Gaussian Process based Tracking Control of Euler-Lagrange Systems”.
In: Automatica 103 (2019), pp. 390–397. doi: 10.1016/j.automatica.2019.01.023. [Preprint] [bibtex] [Video]

T. Beckers, S. Bansal, C. J. Tomlin, and S. Hirche. “Closed-loop Model Selection for Kernel based Models via Bayesian Optimization”.
In: Proceedings of the Conference on Decision and Control. 2019. doi: 10.1109/CDC40024.2019.9029690. [Preprint] [bibtex]

T. Beckers, and S. Hirche. “Keep Soft Robots Soft - a Data-driven based Trade-off between Feed-forward and Feedback Control”.
In:
Robotics: Science and Systems, Workshop on Robust autonomy: tools for safety in real-world uncertain environments. 2019. [Preprint] [bibtex] [Video]

T. Beckers, and S. Hirche. “Gaussian Process based Passivation of a Class of Nonlinear Systems with Unknown Dynamics”.
In: Proceedings of the European Control Conference. 2018. doi: 10.23919/ECC.2018.8550311. [Preprint] [bibtex]

T. Beckers, J. Umlauft, and S. Hirche. “Mean Square Prediction Error of Misspecified Gaussian Process State Space Models”.
In: Proceedings of the Conference on Decision and Control. 2018. doi: 10.1109/CDC.2018.8619163. [Preprint] [bibtex]

J. Umlauft, T. Beckers, and S. Hirche. “A Scenario-based Optimal Control Approach for Gaussian Process State Space Models”.
In: Proceedings of the European Control Conference. 2018. doi: 10.23919/ECC.2018.8550458. [Preprint] [bibtex]

T. Beckers, J. Umlauft, and S. Hirche. “Stable Model-based Control with Gaussian Process Regression for Robot Manipulators”.
In: Proceedings of the IFAC World Congress. 2017. doi: 10.1016/j.ifacol.2017.08.359. [Preprint] [bibtex]

T. Beckers, J. Umlauft, D. Kulić, and S. Hirche. “Stable Gaussian Process based Tracking Control of Lagrangian Systems”.
In: Proceedings of the Conference on Decision and Control. 2017.doi: 10.1109/CDC.2017.8264427. [Preprint] [bibtex] [Video]

J. Umlauft, T. Beckers, M. Kimmel, and S. Hirche. “Feedback Linearization using Gaussian Processes”.
In: Proceedings of the Conference on Decision and Control. IEEE, 2017. doi: 10.1109/CDC.2017.8264435. [Preprint] [bibtex]

T. Beckers, and S. Hirche. “Equilibrium Distributions and Stability Analysis of Gaussian Process State Space Models”.
In: Proceedings of the Conference on Decision and Control. 2016. doi: 10.1109/CDC.2016.7799247. [Preprint] [bibtex]

T. Beckers, and S. Hirche. “Stability of Gaussian Process State Space Models”.
In:
Proceedings of the European Control Conference. 2016. doi: 10.1109/ECC.2016.7810630. [Preprint] [bibtex]

R. Geise, J. Schueuer, L. Thiele, K. Notte, T. Beckers, and A. Enders. “A Slotted Waveguide Setup as Scaled Instrument-Landing-System for Measuring Scattering of an A380 and Large Objects”.
In: Proceedings of the European Conference on Antennas and Propagation. 2010. isbn: 978-84-7653-472-4. [bibtex]


Miscellaneous articles

T. Beckers, L. Colombo, and S. Hirche. “Safe Learning-based Trajectory Tracking for Underactuated Vehicles with Partially Unknown Dynamics”.
arXiv: 2009.06689 [eess.SY]. 2020. [Preprint]

T. Beckers. Gaussian Process based Modeling and Control with Guarantees ”.
Doctoral Dissertation. Technical University of Munich. 2021. [Full text] [bibtex]

T. Beckers. An Introduction to Gaussian Process Models”.
arXiv: 2102.05497 [eess.SY]. 2021. [Full text]

K. Friedl, W. Zhou, M. Rank, A. Ergin, T. Beckers, A. Mahdizadeh, A. Peer, S. Hirche. Haptik von Bedienelementen und Interieurkomponenten im Fahrzeug.
In: DFG Report SFB453 T5. 2014. [bibtex]