CVaR

Uses

How it works

Benefits

Comparisons

Highlighted claims

• The grasping problem is formulated as risk-sensitive belief-space grasping under partial observability. — Variational Neural Belief Parameterizations for Robust Dexterous Grasping under Multimodal Uncertainty
• The risk-sensitive grasp cost uses CVaR over costs sampled from the belief. — Variational Neural Belief Parameterizations for Robust Dexterous Grasping under Multimodal Uncertainty
• The CVaR objective replaces an average-cost target with tail robustness. — Variational Neural Belief Parameterizations for Robust Dexterous Grasping under Multimodal Uncertainty
• The soft CVaR estimator replaces the hinge term with a SoftPlus approximation. — Variational Neural Belief Parameterizations for Robust Dexterous Grasping under Multimodal Uncertainty
• The planner favors grasps that remain robust under adverse friction or contact realizations. — Variational Neural Belief Parameterizations for Robust Dexterous Grasping under Multimodal Uncertainty