A particle-based probabilistic CBF framework derives finite-sample safety certificates for Gaussian state estimation uncertainty by showing that barrier increments remain sub-Gaussian under Lipschitz control-affine dynamics.
Belief control barrier functions for risk-aware control,
2 Pith papers cite this work. Polarity classification is still indexing.
2
Pith papers citing it
years
2026 2verdicts
UNVERDICTED 2representative citing papers
A modular belief-space controller using learned Belief Control Lyapunov Functions for information gathering and conformal-prediction Belief Control Barrier Functions for safety reduces reach-avoid POMDP synthesis to fast quadratic programs.
citing papers explorer
-
Probabilistic Control Barrier Functions for Systems with State Estimation Uncertainty using Sub-Gaussian Concentration
A particle-based probabilistic CBF framework derives finite-sample safety certificates for Gaussian state estimation uncertainty by showing that barrier increments remain sub-Gaussian under Lipschitz control-affine dynamics.
-
Safety-critical Control Under Partial Observability: Reach-Avoid POMDP meets Belief Space Control
A modular belief-space controller using learned Belief Control Lyapunov Functions for information gathering and conformal-prediction Belief Control Barrier Functions for safety reduces reach-avoid POMDP synthesis to fast quadratic programs.