Integrates RL with a differentiable CVaR quadratic-program safety layer to jointly learn nominal controls, risk levels, and margins for adaptive safe navigation under motion uncertainty.
Distributionally robust cvar-based safety filtering for motion planning in uncertain environments,
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
-
Reinforcement Learning for Risk Adaptation via Differentiable CVaR Barrier Functions
Integrates RL with a differentiable CVaR quadratic-program safety layer to jointly learn nominal controls, risk levels, and margins for adaptive safe navigation under motion uncertainty.