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Perception with Guarantees: Certified Pose Estimation via Reachability Analysis

Matthias Althoff, Tobias Ladner, Yasser Shoukry

Formal reachability analysis certifies bounds on 3D poses estimated from camera images of known targets.

arxiv:2602.10032 v2 · 2026-02-10 · cs.CV · cs.RO

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4 Citations open
5 Replications open
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Claims

C1strongest claim

presenting a certified pose estimation in 3D solely from a camera image and a well-known target geometry. This is realized by formally bounding the pose, which is computed by leveraging recent results from reachability analysis and formal neural network verification.

C2weakest assumption

The target geometry is perfectly known and modeled, and the formal verification of the neural network produces sufficiently tight bounds that remain practical for real-time safety-critical decisions.

C3one line summary

Certified 3D pose estimation from camera images using reachability analysis and formal NN verification delivers formal bounds for safety-critical localization.

References

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[1] Journal of the Franklin Institute (2023) 2023
[2] Althoff, M.: Reachability analysis and its application to the safety assessment of autonomous cars. Ph.D. thesis, Technische Universität München (2010) 2010
[3] Althoff, M.: An introduction to CORA 2015. In: Proc. of the 1st and 2nd Workshop on Applied Verification for Continuous and Hybrid Systems. pp. 120–151 (2015) 2015
[4] Foundations and Trends in Machine Learning (2023) 2023
[5] Boldmethod: Runway stripes and markings, explained. (2025), https://www.boldmethod.com/learn-to-fly/regulations/ runway-markings-and-spacing/ 2025

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First computed 2026-05-18T03:09:23.655609Z
Builder pith-number-builder-2026-05-17-v1
Signature Pith Ed25519 (pith-v1-2026-05) · public key
Schema pith-number/v1.0

Canonical hash

2bbb16e9842ddef58717fe7d9e1ebc517732ceaef4c52d6cd5f39dfbed507353

Aliases

arxiv: 2602.10032 · arxiv_version: 2602.10032v2 · doi: 10.48550/arxiv.2602.10032 · pith_short_12: FO5RN2MEFXPP · pith_short_16: FO5RN2MEFXPPLBYX · pith_short_8: FO5RN2ME
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Verify this Pith Number yourself
curl -sH 'Accept: application/ld+json' https://pith.science/pith/FO5RN2MEFXPPLBYX7Z6Z4HV4KF \
  | 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: 2bbb16e9842ddef58717fe7d9e1ebc517732ceaef4c52d6cd5f39dfbed507353
Canonical record JSON
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    "license": "http://creativecommons.org/licenses/by/4.0/",
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