Distilling Privileged Control Barrier Functions into RGB-Only Safety Filters for Dynamic Visual Navigation

arXiv:2609.36520 · cs.RO, cs.CV, cs.SY, eess.SY · Submitted 2026-09-29 · Read on arXiv

cs.RO, cs.CV, cs.SY, eess.SY

Submitted: 2026-09-29

Updated: 2026-09-29

Project page: https://syeon-yoo.github.io/distill-cbf-site

Terminology

• Control Barrier Function — 13× in this paper
• Distillation — 6× in this paper · explained in 2 episodes
• Gaussian Splatting — 6× in this paper · explained in 4 episodes
• Action Space — 4× in this paper · explained in 1 episode
• Reinforcement Learning — 4× in this paper · explained in 4 episodes
• Actor — 3× in this paper · explained in 3 episodes
• Aggregation — 3× in this paper · explained in 1 episode
• IEEE International Conference on Robotics and Automation — 3× in this paper
• Robustness — 3× in this paper · explained in 5 episodes
• Steering — 3× in this paper · explained in 2 episodes
• Ablation — 2× in this paper · explained in 1 episode
• Control Barrier Function (CBF) — 2× in this paper · explained in 5 episodes
• 3D Gaussian Splatting — 1× in this paper · explained in 2 episodes
• Ablation study — 1× in this paper · explained in 1 episode
• Adaptation — 1× in this paper · explained in 1 episode
• Conference on Computer Vision and Pattern Recognition — 1× in this paper
• Conformal Prediction — 1× in this paper · explained in 5 episodes
• Control Barrier Functions (CBFs) — 1× in this paper · explained in 4 episodes
• Deep Reinforcement Learning — 1× in this paper · explained in 2 episodes
• Digital Twin — 1× in this paper · explained in 5 episodes
• Fine-Tuning — 1× in this paper · explained in 5 episodes
• Foundation Model — 1× in this paper · explained in 3 episodes
• Gaussian Splatting (GS) — 1× in this paper · explained in 3 episodes
• Grounding — 1× in this paper · explained in 3 episodes
• Loss Function — 1× in this paper · explained in 2 episodes
• Sim-to-Real Gap — 1× in this paper · explained in 6 episodes
• Zero-Shot Transfer — 1× in this paper · explained in 4 episodes

Sources

• ViNT: A Foundation Model for Visual Navigation
• GNM: A General Navigation Model to Drive Any Robot
• Soft Actor-Critic: Off-Policy Maximum Entropy Deep Reinforcement Learning with a Stochastic Actor

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