Publications
Journal Papers
L. Brunke, S. Zhou, M. Che, A.P. Schoellig, “Optimized Control Invariance Conditions for Uncertain Input-Constrained Nonlinear Control Systems,” in IEEE Control Systems Letters, 8, 157-162, 2024. [paper] [preprint] [video]
S. Zhou, L. Brunke, A. Tao, A.W. Hall, F. Pizarro Bejarano, J. Panerati, A.P. Schoellig, “What is the Impact of Releasing Code with Publications? Statistics from the Machine Learning, Robotics, and Control Communities, “ in IEEE Control Systems Magazine, 2024 (to appear). [preprint]
Z. Yuan, A. W. Hall, S. Zhou, L. Brunke, M. Greeff, J. Panerati, A.P. Schoellig, “safe-control-gym: a Unified Benchmark Suite for Safe Learning-based Control and Reinforcement Learning,” in IEEE Robotics and Automation Letters, 7:4, 11142-11149, 2022. [paper] [preprint]
L. Brunke, M. Greeff, A.W. Hall, Z. Yuan, S. Zhou, J. Panerati, A.P. Schoellig, “Safe Learning in Robotics: From Learning-Based Control to Safe Reinforcement Learning,” in Annual Review of Control, Robotics, and Autonomous Systems, 5:1, 411-444, 2022. [paper] [preprint] [talk]
K. Pereida, L. Brunke, A.P. Schoellig, “Robust Adaptive Model Predictive Control for Guaranteed Fast and Accurate Stabilization in the Presence of Model Eerrors,” in Int J Robust Nonlinear Control, 31: 8750– 8784, 2021. [paper] [preprint]
M. Cordes, L. Brunke, and W. Hintze, “Correction to: Offline simulation of path deviation due to joint compliance and hysteresis for robot machining,” in The International Journal of Advanced Manufacturing Technology, 2019. [paper]
Conference Papers
L. Brunke, S. Zhou, M. Che, A.P. Schoellig, “Practical Considerations for Discrete-Time Implementations of Continuous-Time Control Barrier Function-Based Safety Filters,” in 2024 IEEE American Control Conference, 2024 (to appear). [preprint] [video]
R. Römer, L. Brunke, S. Zhou, A. P. Schoellig “Is Data All That Matters? The Role of Control Frequency for Learning-Based Sampled-Data Control of Uncertain Systems,” in 2024 IEEE American Control Conference, 2024 (to appear). [preprint]
F. Pizarro Bejarano, L. Brunke, A.P. Schoellig, “Multi-Step Model Predictive Safety Filters: Reducing Chattering by Increasing the Prediction Horizon,” in Proceedings of the 62nd IEEE Conference on Decision and Control, 2023. [paper] [preprint] [video]
L. Brunke, S. Zhou, A.P. Schoellig, “Robust Predictive Output-Feedback Safety Filter for Uncertain Nonlinear Control Systems,” in Proceedings of the 61st IEEE Conference on Decision and Control, 2022. [paper] [preprint]
L. Brunke, S. Zhou, A.P. Schoellig, “Barrier Bayesian Linear Regression: Online Learning of Control Barrier Conditions for Safety-Critical Control of Uncertain Systems,” in Proceedings of The 4th Annual Learning for Dynamics and Control Conference, PMLR 168:881-892, 2022. [paper] [preprint]
L. Brunke, S. Zhou, A.P. Schoellig, “RLO-MPC: Robust Learning-Based Output Feedback MPC for Improving the Performance of Uncertain Systems in Iterative Tasks,” in Proceedings of the 60th IEEE Conference on Decision and Control, 2021. [paper] [preprint] [talk]
Workshop Papers
R. Römer, L. Brunke, M. Schuck, A. P. Schoellig “Safe Offline Reinforcement Learning using Trajectory-Level Diffusion Models,” in ICRA 2024 Workshop—Back to the Future: Robot Learning Going Probabilistic, 2024. [preprint]
A. Jiao, T.P. Patel, S. Khurana, A. Korol, L. Brunke, V. K. Adajania, U. Culha, S. Zhou, A.P. Schoellig, “Swarm-GPT: Combining Large Language Models with Safe Motion Planning for Robot Choreography Design,” in 6th Robot Learning Workshop: Pretraining, Fine-Tuning, and Generalization with Large Scale Models, 2023. [preprint]
L. Brunke, P. Agrawal, N. George, “Evaluating Input Perturbation Methods for Interpreting CNNs and Saliency Map Comparison,” in Proceedings of the European Conference on Computer Vision (ECCV) Workshops, 2020; 12535: 120-134. [paper] [preprint]
Preprints
S. Teetaert, W. Zhao, N. Xinyuan, H. Zahir, H. Leong, M. Hidalgo, G. Puga, T. Lorente, N. Espinosa, J.A. Duarte Carrasco, K. Zhang, J. Di, T. Jin, X. Li, Y. Zhou, X. Liang, C. Zhang, A. Loquercio, S. Zhou, L. Brunke, M. Greeff, W. Hoenig, J. Panerati, A.P. Schoellig, “A Remote Sim2real Aerial Competition: Fostering Reproducibility and Solutions’ Diversity in Robotics Challenges,” 2023. [preprint]
Theses
L. Brunke, “Learning Model Predictive Control for Competitive Autonomous Racing,” Master’s thesis, Hamburg, 2018. [preprint]
Supervisors: Prof. Francesco Borrelli (UC Berkeley), Ugo Rosolia (UC Berkeley)
Examiners: Prof. Robert Seifried (TUHH), Prof. Herbert Werner (TUHH)
L. Brunke, “Interpretation of Convolutional Neural Networks,” Project thesis, Hamburg, 2017.
Supervisors: Prof. Alexander Schlaefer (TUHH), Silviu Homoceanu (Volkswagen)
L. Brunke, “Identification and Modeling of Backlash in Robot Transmissions,” Bachelor’s thesis, Hamburg, 2015.
Supervisors: Prof. Wolfgang Hintze (TUHH), Marcel Cordes (TUHH)