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pith:ZXRVF237

pith:2026:ZXRVF237F53ZA32RMPJTGOEEII
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SODA-CitrON: Static Object Data Association by Clustering Multi-Modal Sensor Detections Online

Jan Nausner, Kilian Wohlleben, Michael Hubner

SODA-CitrON clusters multi-modal detections online to associate and track static objects without motion models or known counts.

arxiv:2602.22243 v3 · 2026-02-24 · cs.RO

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Claims

C1strongest claim

The results demonstrate that SODA-CitrON consistently outperforms the compared methods in terms of F1 score, position RMSE, MOTP, and MOTA in the static object mapping scenarios studied.

C2weakest assumption

The Monte Carlo simulation scenarios used for evaluation are representative of real-world conditions involving temporally uncorrelated, multi-sensor measurements with heterogeneous uncertainties.

C3one line summary

SODA-CitrON performs online clustering of heterogeneous sensor detections to associate and track static objects, outperforming JPDA, DBSTREAM, and POM-based methods on F1 score, position RMSE, MOTP, and MOTA in Monte Carlo simulations.

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First computed 2026-06-09T02:07:22.058181Z
Builder pith-number-builder-2026-05-17-v1
Signature Pith Ed25519 (pith-v1-2026-05) · public key
Schema pith-number/v1.0

Canonical hash

cde352eb7f2f77906f5163d333388442345914b1c8be78f12cad9fe51d1b6d35

Aliases

arxiv: 2602.22243 · arxiv_version: 2602.22243v3 · doi: 10.48550/arxiv.2602.22243 · pith_short_12: ZXRVF237F53Z · pith_short_16: ZXRVF237F53ZA32R · pith_short_8: ZXRVF237
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curl -sH 'Accept: application/ld+json' https://pith.science/pith/ZXRVF237F53ZA32RMPJTGOEEII \
  | 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: cde352eb7f2f77906f5163d333388442345914b1c8be78f12cad9fe51d1b6d35
Canonical record JSON
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