Lukas Brunke
Lukas Brunke
PhD Candidate, University of Toronto and Technical University of Munich
Verified email at - Homepage
Cited by
Cited by
Safe learning in robotics: From learning-based control to safe reinforcement learning
L Brunke, M Greeff, AW Hall, Z Yuan, S Zhou, J Panerati, AP Schoellig
Annual Review of Control, Robotics, and Autonomous Systems 5, 2021
Correction to: Offline simulation of path deviation due to joint compliance and hysteresis for robot machining
M Cordes, L Brunke, W Hintze
The International Journal of Advanced Manufacturing Technology 105 (7-8 …, 2019
safe-Control-Gym: A Unified Benchmark Suite for Safe Learning-Based Control and Reinforcement Learning in Robotics
Z Yuan, AW Hall, S Zhou, L Brunke, M Greeff, J Panerati, AP Schoellig
IEEE Robotics and Automation Letters, 2022
Barrier Bayesian Linear Regression: Online Learning of Control Barrier Conditions for Safety-Critical Control of Uncertain Systems
L Brunke, S Zhou, AP Schoellig
Learning for Dynamics and Control Conference, 881-892, 2022
Robust adaptive model predictive control for guaranteed fast and accurate stabilization in the presence of model errors
K Pereida, L Brunke, AP Schoellig
International Journal of Robust and Nonlinear Control, 2021
Evaluating input perturbation methods for interpreting CNNs and saliency map comparison
L Brunke, P Agrawal, N George
Computer Vision–ECCV 2020 Workshops: Glasgow, UK, August 23–28, 2020 …, 2020
RLO-MPC: Robust learning-based output feedback MPC for improving the performance of uncertain systems in iterative tasks
L Brunke, S Zhou, AP Schoellig
2021 60th IEEE Conference on Decision and Control (CDC), 2183-2190, 2021
Multi-Step Model Predictive Safety Filters: Reducing Chattering by Increasing the Prediction Horizon
FP Bejarano, L Brunke, AP Schoellig
2023 62nd IEEE Conference on Decision and Control (CDC), 4723-4730, 2023
Robust Predictive Output-Feedback Safety Filter for Uncertain Nonlinear Control Systems
L Brunke, S Zhou, AP Schoellig
2022 IEEE 61st Conference on Decision and Control (CDC), 3051-3058, 2022
Learning Model Predictive Control for Competitive Autonomous Racing
L Brunke
arXiv preprint arXiv:2005.00826, 2020
Swarm-GPT: Combining Large Language Models with Safe Motion Planning for Robot Choreography Design
A Jiao, TP Patel, S Khurana, AM Korol, L Brunke, VK Adajania, U Culha, ...
arXiv preprint arXiv:2312.01059, 2023
Optimized Control Invariance Conditions for Uncertain Input-Constrained Nonlinear Control Systems
L Brunke, S Zhou, M Che, AP Schoellig
IEEE Control Systems Letters, 2023
What is the Impact of Releasing Code with Publications? Statistics from the Machine Learning, Robotics, and Control Communities
S Zhou, L Brunke, A Tao, AW Hall, FP Bejarano, J Panerati, AP Schoellig
arXiv preprint arXiv:2308.10008, 2023
Practical Considerations for Discrete-Time Implementations of Continuous-Time Control Barrier Function-Based Safety Filters
L Brunke, S Zhou, M Che, AP Schoellig
arXiv preprint arXiv:2404.12329, 2024
Is Data All That Matters? The Role of Control Frequency for Learning-Based Sampled-Data Control of Uncertain Systems
R Römer, L Brunke, S Zhou, AP Schoellig
arXiv preprint arXiv:2403.09504, 2024
A Remote Sim2real Aerial Competition: Fostering Reproducibility and Solutions' Diversity in Robotics Challenges
S Teetaert, W Zhao, N Xinyuan, H Zahir, H Leong, M Hidalgo, G Puga, ...
arXiv preprint arXiv:2308.16743, 2023
Safe Offline Reinforcement Learning using Trajectory-Level Diffusion Models
R Römer, L Brunke, M Schuck, AP Schoellig
ICRA 2024 Workshop {\textemdash} Back to the Future: Robot Learning Going …, 0
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