A conformal prediction certification for belief-space safety filters focuses verification on reliable inference regions to produce less conservative yet high-probability safe filters than standard baselines in human-vehicle simulations.
Set invariance in control
2 Pith papers cite this work, alongside 2,340 external citations. Polarity classification is still indexing.
2
Pith papers citing it
2,340
external citations · OpenAlex
years
2026 2verdicts
UNVERDICTED 2representative citing papers
Sigmoid-based constraint lifting transforms state-constrained discrete-time nonlinear systems into unconstrained backstepping designs that guarantee asymptotic stability and forward invariance of the safe set.
citing papers explorer
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Permissive Safety Through Trusted Inference: Verifiable Belief-Space Neural Safety Filters for Assured Interactive Robotics
A conformal prediction certification for belief-space safety filters focuses verification on reliable inference regions to produce less conservative yet high-probability safe filters than standard baselines in human-vehicle simulations.
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State-Constrained Control of Discrete-Time Nonlinear Systems via Constraint Lifting
Sigmoid-based constraint lifting transforms state-constrained discrete-time nonlinear systems into unconstrained backstepping designs that guarantee asymptotic stability and forward invariance of the safe set.