Time-varying stochastic barrier certificates capture temporal obstacle dynamics via Bellman optimality to deliver tighter probabilistic safety bounds than prior methods, formulated as convex sum-of-squares programs.
Training with hard constraints: Learning neural certificates and con- trollers for sdes
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
fields
cs.RO 1years
2026 1verdicts
UNVERDICTED 1representative citing papers
citing papers explorer
-
Stochastic Barrier Certificates in the Presence of Dynamic Obstacles
Time-varying stochastic barrier certificates capture temporal obstacle dynamics via Bellman optimality to deliver tighter probabilistic safety bounds than prior methods, formulated as convex sum-of-squares programs.