HJ-SafeDMP learns a control barrier value function offline from demonstrations via finite-difference HJ recursion and uses it as a closed-form safety filter on DMP outputs, with conformal prediction for coverage guarantees.
and Bansal, Somil , booktitle =
2 Pith papers cite this work. Polarity classification is still indexing.
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Generative sequence models for physical tasks exhibit physical misgeneralization where local prediction errors propagate through physical measurements to distort aggregate distributions over quantities like distance or energy; a data deviation kernel explains and predicts the shifts and supports a内核
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HJ-SafeDMP: Hamilton-Jacobi Reachability-Guided Dynamic Movement Primitives for Provably Safe Robot Motion
HJ-SafeDMP learns a control barrier value function offline from demonstrations via finite-difference HJ recursion and uses it as a closed-form safety filter on DMP outputs, with conformal prediction for coverage guarantees.
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Mechanisms of Misgeneralization in Physical Sequence Modeling
Generative sequence models for physical tasks exhibit physical misgeneralization where local prediction errors propagate through physical measurements to distort aggregate distributions over quantities like distance or energy; a data deviation kernel explains and predicts the shifts and supports a内核