pith:HIV6RJ7H
Distributionally Robust Safety Under Arbitrary Uncertainties: A Safety Filtering Approach
Backup-based safety filtering reduces distributionally robust certification to a one-dimensional search over switching time.
arxiv:2605.12974 v1 · 2026-05-13 · cs.RO · cs.SY · eess.SY
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\pithnumber{HIV6RJ7HTXKCA5TYO376C5I6W2}
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Claims
we exploit the structure of backup-based safety filtering to reduce safety certification to a one-dimensional search over the switching time between nominal and backup policies. We then develop a sampling-based certification procedure with finite-sample guarantees, where empirical failure probabilities are compared against a Wasserstein-inflated threshold.
The true uncertainty distribution lies within the chosen Wasserstein ambiguity set around the empirical distribution, and the backup policy remains certified safe under the worst-case distribution in that set.
A backup-based safety filter combined with Wasserstein ambiguity sets reduces probabilistic safety certification for nonlinear systems to a one-dimensional search with finite-sample guarantees.
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| First computed | 2026-05-18T03:09:08.787106Z |
|---|---|
| Builder | pith-number-builder-2026-05-17-v1 |
| Signature | Pith Ed25519
(pith-v1-2026-05) · public key |
| Schema | pith-number/v1.0 |
Canonical hash
3a2be8a7e79dd420767876ffe1751eb69e0a3c8b6c39a9123515f92c0b95f6b0
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· · · · ·Agent API
Verify this Pith Number yourself
curl -sH 'Accept: application/ld+json' https://pith.science/pith/HIV6RJ7HTXKCA5TYO376C5I6W2 \
| jq -c '.canonical_record' \
| python3 -c "import sys,json,hashlib; b=json.dumps(json.loads(sys.stdin.read()), sort_keys=True, separators=(',',':'), ensure_ascii=False).encode(); print(hashlib.sha256(b).hexdigest())"
# expect: 3a2be8a7e79dd420767876ffe1751eb69e0a3c8b6c39a9123515f92c0b95f6b0
Canonical record JSON
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