Header logo is


2017


Thumb xl fig toyex lqr1kernel 1
On the Design of LQR Kernels for Efficient Controller Learning

Marco, A., Hennig, P., Schaal, S., Trimpe, S.

Proceedings of the 56th IEEE Annual Conference on Decision and Control (CDC), pages: 5193-5200, IEEE, IEEE Conference on Decision and Control, December 2017 (conference)

Abstract
Finding optimal feedback controllers for nonlinear dynamic systems from data is hard. Recently, Bayesian optimization (BO) has been proposed as a powerful framework for direct controller tuning from experimental trials. For selecting the next query point and finding the global optimum, BO relies on a probabilistic description of the latent objective function, typically a Gaussian process (GP). As is shown herein, GPs with a common kernel choice can, however, lead to poor learning outcomes on standard quadratic control problems. For a first-order system, we construct two kernels that specifically leverage the structure of the well-known Linear Quadratic Regulator (LQR), yet retain the flexibility of Bayesian nonparametric learning. Simulations of uncertain linear and nonlinear systems demonstrate that the LQR kernels yield superior learning performance.

am ics pn

arXiv PDF On the Design of LQR Kernels for Efficient Controller Learning - CDC presentation DOI Project Page [BibTex]

2017


arXiv PDF On the Design of LQR Kernels for Efficient Controller Learning - CDC presentation DOI Project Page [BibTex]


Thumb xl teaser
Optimizing Long-term Predictions for Model-based Policy Search

Doerr, A., Daniel, C., Nguyen-Tuong, D., Marco, A., Schaal, S., Toussaint, M., Trimpe, S.

Proceedings of 1st Annual Conference on Robot Learning (CoRL), 78, pages: 227-238, (Editors: Sergey Levine and Vincent Vanhoucke and Ken Goldberg), 1st Annual Conference on Robot Learning, November 2017 (conference)

Abstract
We propose a novel long-term optimization criterion to improve the robustness of model-based reinforcement learning in real-world scenarios. Learning a dynamics model to derive a solution promises much greater data-efficiency and reusability compared to model-free alternatives. In practice, however, modelbased RL suffers from various imperfections such as noisy input and output data, delays and unmeasured (latent) states. To achieve higher resilience against such effects, we propose to optimize a generative long-term prediction model directly with respect to the likelihood of observed trajectories as opposed to the common approach of optimizing a dynamics model for one-step-ahead predictions. We evaluate the proposed method on several artificial and real-world benchmark problems and compare it to PILCO, a model-based RL framework, in experiments on a manipulation robot. The results show that the proposed method is competitive compared to state-of-the-art model learning methods. In contrast to these more involved models, our model can directly be employed for policy search and outperforms a baseline method in the robot experiment.

am ics

PDF Project Page [BibTex]

PDF Project Page [BibTex]


Thumb xl apollo system2 croped
Model-Based Policy Search for Automatic Tuning of Multivariate PID Controllers

Doerr, A., Nguyen-Tuong, D., Marco, A., Schaal, S., Trimpe, S.

In Proceedings of the IEEE International Conference on Robotics and Automation (ICRA), pages: 5295-5301, IEEE, Piscataway, NJ, USA, IEEE International Conference on Robotics and Automation (ICRA), May 2017 (inproceedings)

am ics

PDF arXiv DOI Project Page [BibTex]

PDF arXiv DOI Project Page [BibTex]


Thumb xl this one
Virtual vs. Real: Trading Off Simulations and Physical Experiments in Reinforcement Learning with Bayesian Optimization

Marco, A., Berkenkamp, F., Hennig, P., Schoellig, A. P., Krause, A., Schaal, S., Trimpe, S.

In Proceedings of the IEEE International Conference on Robotics and Automation (ICRA), pages: 1557-1563, IEEE, Piscataway, NJ, USA, IEEE International Conference on Robotics and Automation (ICRA), May 2017 (inproceedings)

am ics pn

PDF arXiv ICRA 2017 Spotlight presentation Virtual vs. Real - Video explanation DOI Project Page [BibTex]

PDF arXiv ICRA 2017 Spotlight presentation Virtual vs. Real - Video explanation DOI Project Page [BibTex]

2014


no image
A Self-Tuning LQR Approach Demonstrated on an Inverted Pendulum

Trimpe, S., Millane, A., Doessegger, S., D’Andrea, R.

In Proceedings of the 19th IFAC World Congress, Cape Town, South Africa, 2014 (inproceedings)

am ics

PDF Supplementary material DOI [BibTex]

2014


PDF Supplementary material DOI [BibTex]


no image
Stability Analysis of Distributed Event-Based State Estimation

Trimpe, S.

In Proceedings of the 53rd IEEE Conference on Decision and Control, Los Angeles, CA, 2014 (inproceedings)

Abstract
An approach for distributed and event-based state estimation that was proposed in previous work [1] is analyzed and extended to practical networked systems in this paper. Multiple sensor-actuator-agents observe a dynamic process, sporadically exchange their measurements over a broadcast network according to an event-based protocol, and estimate the process state from the received data. The event-based approach was shown in [1] to mimic a centralized Luenberger observer up to guaranteed bounds, under the assumption of identical estimates on all agents. This assumption, however, is unrealistic (it is violated by a single packet drop or slight numerical inaccuracy) and removed herein. By means of a simulation example, it is shown that non-identical estimates can actually destabilize the overall system. To achieve stability, the event-based communication scheme is supplemented by periodic (but infrequent) exchange of the agentsâ?? estimates and reset to their joint average. When the local estimates are used for feedback control, the stability guarantee for the estimation problem extends to the event-based control system.

am ics

PDF Supplementary material DOI Project Page [BibTex]

PDF Supplementary material DOI Project Page [BibTex]


no image
Increasing the sensor performance using Au modified high temperature superconducting YBa2Cu3O7-delta thin films

Katzer, C., Stahl, C., Michalowski, P., Treiber, S., Westernhausen, M., Schmidl, F., Seidel, P., Schütz, G., Albrecht, J.

In 507, IOP Pub., Genova, Italy, 2014 (inproceedings)

mms

DOI [BibTex]

DOI [BibTex]

2010


no image
Absence of element specific ferromagnetism in Co doped ZnO investigated by soft X-ray resonant reflectivity

Goering, E., Brück, S., Tietze, T., Jakob, G., Gacic, M., Adrian, H.

In 200, Glasgow, Scotland, 2010 (inproceedings)

mms

DOI [BibTex]

2010


DOI [BibTex]


no image
Probing the local magnetization dynamics in large systems with spatial inhomogeneity

Li, J, Lee, M.-S., Amaladass, E., He, W., Eimüller, T.

In 200, Glasgow, Scotland, 2010 (inproceedings)

mms

DOI [BibTex]

DOI [BibTex]


no image
Wetting of grain boundaries in Al by the solid Al3Mg2 phase

Straumal, B. B., Baretzky, B., Kogtenkova, O. A., Straumal, A. B., Sidorenko, A. S.

In 45, pages: 2057-2061, Athens, Greek, 2010 (inproceedings)

mms

DOI [BibTex]

DOI [BibTex]


no image
Damping of near-adiabatic magnetization dynamics by excitations of electron-hole pairs

Seib, J., Steiauf, D., Fähnle, M.

In 200, Karlsruhe, Germany, 2010 (inproceedings)

mms

DOI [BibTex]

DOI [BibTex]


no image
Magnetization reversal of Fe/Gd multilayers on self-assembled arrays of nanospheres

Amaladass, E., Eimüller, T., Ludescher, B., Tyliszczak, T., Schütz, G.

In 200, Glasgow, Scotland, 2010 (inproceedings)

mms

DOI [BibTex]

DOI [BibTex]


no image
Contact angles by the solid-phase grain boundary wetting (coverage) in the Co-Cu system

Straumal, B. B., Kogtenkova, O. A., Straumal, A. B., Kuchyeyev, Y. O., Baretzky, B.

In 45, pages: 4271-4275, Glasgow, Scotland, 2010 (inproceedings)

mms

DOI [BibTex]

DOI [BibTex]


no image
Unusual super-ductility at room temperature in an ultrafine-grained aluminum alloy

Valiev, R. Z., Murashkin, M. Y., Kilmametov, A., Straumal, B., Chinh, N. Q., Langdon, T.

In 45, pages: 4718-4724, Seattle, WA, USA, 2010 (inproceedings)

mms

DOI [BibTex]

DOI [BibTex]


no image
Demagnetization on the fs time-scale by the Elliott-Yafet mechanism

Steiauf, D., Illg, C., Fähnle, M.

In 200, Karlsruhe, Germany, 2010 (inproceedings)

mms

DOI [BibTex]

DOI [BibTex]


no image
The X-ray microscopy beamline UE46-PGM2 at BESSY

Follath, R., Schmidt, J. S., Weigand, M., Fauth, K.

In 10th International Conference on Synchrotron Radiation Instrumentation, 1234, pages: 323-326, AIP Conference Proceedings, American Institute of Physics, Melbourne, Australia, 2010 (inproceedings)

mms

DOI [BibTex]

DOI [BibTex]