CI-MSE improves Spearman's rank correlation between offline validation error and real rollout performance from -0.61 (raw MSE) to -0.87 across policy checkpoints in simulation and real-world robot manipulation experiments.
A Survey on Imitation Learning for Contact-Rich Tasks in Robotics
2 Pith papers cite this work, alongside 3 external citations. Polarity classification is still indexing.
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cs.RO 2years
2026 2verdicts
UNVERDICTED 2representative citing papers
SafePBDS uses pullback control barrier functions and a task manifold action interface to generate certifiably safe, steerable motions on high-DOF robots from objectives defined on arbitrary geometric spaces.
citing papers explorer
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Critical Interval MSE: Toward Reliable Offline Validation for Robot Manipulation Policies
CI-MSE improves Spearman's rank correlation between offline validation error and real rollout performance from -0.61 (raw MSE) to -0.87 across policy checkpoints in simulation and real-world robot manipulation experiments.
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Safe and Steerable Geometric Motion Policies for Robotic Dexterous Manipulation
SafePBDS uses pullback control barrier functions and a task manifold action interface to generate certifiably safe, steerable motions on high-DOF robots from objectives defined on arbitrary geometric spaces.