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Sebastian Trimpe
Sebastian Trimpe
Professor, RWTH Aachen University
E-mail confirmado em dsme.rwth-aachen.de - Página inicial
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Ano
Event-based state estimation with variance-based triggering
S Trimpe, R D'Andrea
IEEE Transactions on Automatic Control 59 (12), 3266-3281, 2014
2862014
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
2862012
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
2792018
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
2192020
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
2112016
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
1702017
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
1502018
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
1302019
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
1162018
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
962016
Actively learning gaussian process dynamics
M Buisson-Fenet, F Solowjow, S Trimpe
Learning for dynamics and control, 5-15, 2020
922020
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
882011
Practical and rigorous uncertainty bounds for Gaussian process regression
C Fiedler, CW Scherer, S Trimpe
Proceedings of the AAAI conference on artificial intelligence 35 (8), 7439-7447, 2021
802021
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
772019
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
772018
Wireless control for smart manufacturing: Recent approaches and open challenges
D Baumann, F Mager, U Wetzker, L Thiele, M Zimmerling, S Trimpe
Proceedings of the IEEE 109 (4), 441-467, 2020
722020
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
662014
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
652010
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
622017
Sliding mode control with gaussian process regression for underwater robots
GS Lima, S Trimpe, WM Bessa
Journal of Intelligent & Robotic Systems 99 (3), 487-498, 2020
532020
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