14 citations · 35 across the 21 of their papers we have counts for
8 papers · 1 filter
Addressing Relative Degree Issues in Control Barrier Function Synthesis with Physics-Informed Neural Networks
Lukas Brunke, Siqi Zhou, Francesco D'Orazio +1
In robotics, control barrier function (CBF)-based safety filters are commonly used to enforce state constraints. A critical challenge arises when the relative degree of the CBF var…
Preventing Inactive CBF Safety Filters Caused by Invalid Relative Degree Assumptions
Lukas Brunke, Siqi Zhou, Angela P. Schoellig
Control barrier function (CBF) safety filters emerged as a popular framework to certify and modify potentially unsafe control inputs, for example, provided by a reinforcement learn…
Practical Considerations for Discrete-Time Implementations of Continuous-Time Control Barrier Function-Based Safety Filters
Lukas Brunke, Siqi Zhou, Mingxuan Che +1
Safety filters based on control barrier functions (CBFs) have become a popular method to guarantee safety for uncertified control policies, e.g., as resulting from reinforcement le…
Is Data All That Matters? The Role of Control Frequency for Learning-Based Sampled-Data Control of Uncertain Systems
Ralf Römer, Lukas Brunke, Siqi Zhou +1
Learning models or control policies from data has become a powerful tool to improve the performance of uncertain systems. While a strong focus has been placed on increasing the amo…
Optimized Control Invariance Conditions for Uncertain Input-Constrained Nonlinear Control Systems
Lukas Brunke, Siqi Zhou, Mingxuan Che +1
Providing safety guarantees for learning-based controllers is important for real-world applications. One approach to realizing safety for arbitrary control policies is safety filte…
What is the Impact of Releasing Code with Publications? Statistics from the Machine Learning, Robotics, and Control Communities
Siqi Zhou, Lukas Brunke, Allen Tao +4
Open-sourcing research publications is a key enabler for the reproducibility of studies and the collective scientific progress of a research community. As all fields of science dev…
Robust Predictive Output-Feedback Safety Filter for Uncertain Nonlinear Control Systems
Lukas Brunke, Siqi Zhou, Angela P. Schoellig
In real-world applications, we often require reliable decision making under dynamics uncertainties using noisy high-dimensional sensory data. Recently, we have seen an increasing n…
RLO-MPC: Robust Learning-Based Output Feedback MPC for Improving the Performance of Uncertain Systems in Iterative Tasks
Lukas Brunke, Siqi Zhou, Angela P. Schoellig
In this work we address the problem of performing a repetitive task when we have uncertain observations and dynamics. We formulate this problem as an iterative infinite horizon opt…