Sebastian Trimpe

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Dominik BaumannAalto University, Espoo, FinlandVerified email at aalto.fi
Stefan SchaalRobotics, Machine Learning, AI, NeuroscienceVerified email at google.com
Friedrich SolowjowRWTH Aachen UniversityVerified email at dsme.rwth-aachen.de
Alonso MarcoUniversity of California BerkeleyVerified email at berkeley.edu
Raffaello D'AndreaETH ZurichVerified email at ethz.ch
Philipp HennigUniversity of Tübingen & Max Planck Institute for Intelligent SystemsVerified email at tue.mpg.de
Frank AllgöwerUniversity of StuttgartVerified email at ist.uni-stuttgart.de
Marco ZimmerlingProfessor, TU DarmstadtVerified email at tu-darmstadt.de
Fabian MagerPhD Student, Networked Embedded Systems Lab, TU DresdenVerified email at tu-dresden.de
Jeannette BohgAssistant Professor, Stanford UniversityVerified email at stanford.edu
Johannes KöhlerPostDoc at ETH ZurichVerified email at ethz.ch
Duy Nguyen-TuongBosch Center for AI, GermanyVerified email at robot-learning.de
Christian DanielBosch Center for Artificial IntelligenceVerified email at ias.tu-darmstadt.de
Alexander von RohrRWTH Aachen UniversityVerified email at dsme.rwth-aachen.de
Andreas DoerrSenior Applied Scientist @ Amazon AWS, ex. Bosch Center for AI, MPI for Intelligent SystemsVerified email at tuebingen.mpg.de
Andreas KrauseProfessor of Computer Science, ETH ZurichVerified email at inf.ethz.ch
Marc ToussaintProfessor of Computer Science, TU Berlin, GermanyVerified email at tu-berlin.de
Lothar ThieleProfessor of Computer Engineering, ETH ZurichVerified email at ethz.ch
Mona Buisson-FenetPhD Student, Mines Paris, Centre Automatique et SystèmesVerified email at mines-paristech.fr
Cristina Garcia CifuentesMax Planck Institute for Intelligent SystemsVerified email at tue.mpg.de

Sebastian Trimpe

Professor, RWTH Aachen University

Verified email at dsme.rwth-aachen.de - Homepage

Control Machine Learning Networked Systems Robotics


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Event-based state estimation with variance-based triggering S Trimpe, R D'Andrea IEEE Transactions on Automatic Control 59 (12), 3266-3281, 2014	248	2014
Event-based state estimation with variance-based triggering S Trimpe, R D'Andrea Decision and Control (CDC), 2012 IEEE 51st Annual Conference on, 6583-6590, 2012	248	2012
Learning an approximate model predictive controller with guarantees M Hertneck, J Köhler, S Trimpe, F Allgöwer IEEE Control Systems Letters 2 (3), 543-548, 2018	189	2018
Automatic LQR tuning based on Gaussian process global optimization A Marco, P Hennig, J Bohg, S Schaal, S Trimpe Robotics and Automation (ICRA), 2016 IEEE International Conference on, 270-277, 2016	149	2016
Virtual vs. real: Trading off simulations and physical experiments in reinforcement learning with Bayesian optimization A Marco, F Berkenkamp, P Hennig, AP Schoellig, A Krause, S Schaal, ... 2017 IEEE International Conference on Robotics and Automation (ICRA), 1557-1563, 2017	131	2017
Probabilistic recurrent state-space models A Doerr, C Daniel, M Schiegg, D Nguyen-Tuong, S Schaal, M Toussaint, ... International Conference on Machine Learning (ICML) 80, 1280-1289, 2018	109	2018
Safe and fast tracking on a robot manipulator: Robust mpc and neural network control J Nubert, J Köhler, V Berenz, F Allgöwer, S Trimpe IEEE Robotics and Automation Letters 5 (2), 3050-3057, 2020	103	2020
An experimental demonstration of a distributed and event-based state estimation algorithm S Trimpe, R D'Andrea IFAC Proceedings Volumes 44 (1), 8811-8818, 2011	82	2011
Learning-based robust model predictive control with state-dependent uncertainty R Soloperto, MA Müller, S Trimpe, F Allgöwer IFAC-PapersOnLine 51 (20), 442-447, 2018	79	2018
Data-efficient autotuning with bayesian optimization: An industrial control study M Neumann-Brosig, A Marco, D Schwarzmann, S Trimpe IEEE Transactions on Control Systems Technology 28 (3), 730-740, 2019	73	2019
Depth-based object tracking using a robust gaussian filter J Issac, M Wüthrich, CG Cifuentes, J Bohg, S Trimpe, S Schaal 2016 IEEE International Conference on Robotics and Automation (ICRA), 608-615, 2016	66	2016
Feedback control goes wireless: Guaranteed stability over low-power multi-hop networks F Mager, D Baumann, R Jacob, L Thiele, S Trimpe, M Zimmerling Proceedings of the 10th ACM/IEEE International Conference on Cyber-Physical …, 2019	61	2019
A Self-Tuning LQR Approach Demonstrated on an Inverted Pendulum S Trimpe, A Millane, S Doessegger, R D’Andrea Proc. of the 19th IFAC World Congress, 2014	59	2014
Accelerometer-based tilt estimation of a rigid body with only rotational degrees of freedom S Trimpe, R D'Andrea 2010 IEEE International Conference on Robotics and Automation, 2630-2636, 2010	58	2010
Deep reinforcement learning for event-triggered control D Baumann, JJ Zhu, G Martius, S Trimpe 2018 IEEE Conference on Decision and Control (CDC), 943-950, 2018	53	2018
Distributed event-based state estimation for networked systems: An LMI approach M Muehlebach, S Trimpe IEEE Transactions on Automatic Control 63 (1), 269-276, 2017	48	2017
Actively learning gaussian process dynamics M Buisson-Fenet, F Solowjow, S Trimpe Learning for dynamics and control, 5-15, 2020	47	2020
On the Choice of the Event Trigger in Event-based Estimation S Trimpe, MC Campi Event-based Control, Communication, and Signal Processing (EBCCSP), 2015 …, 2015	45	2015
The balancing cube: A dynamic sculpture as test bed for distributed estimation and control S Trimpe, R D’Andrea IEEE Control Systems Magazine 32 (6), 48-75, 2012	44	2012
Optimizing Long-term Predictions for Model-based Policy Search A Doerr, C Daniel, D Nguyen-Tuong, A Marco, S Schaal, M Toussaint, ... Conference on Robot Learning, 227-238, 2017	38	2017

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