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Blake Werner

2 accepted papers

2026

CBF-RL: Safety Filtering Reinforcement Learning in Training with Control Barrier Functions

ICRA 2026poster

Reinforcement learning (RL), while powerful and expressive, can often prioritize performance at the expense of safety. Yet safety violations can lead to catastrophic outcomes in real-world deployments. Control Barrier Functions (CBFs) offer a principled method to enforce dynamic safety—traditionally…

2025

SHIELD: Safety on Humanoids via CBFs In Expectation on Learned Dynamics

IROS 2025

Robot learning has produced remarkably effective "black-box" controllers for complex tasks such as dynamic locomotion on humanoids. Yet ensuring dynamic safety, i.e., constraint satisfaction, remains challenging for such policies. Reinforcement learning (RL) embeds constraints heuristically through

Cited by 4SourceScholar