pith:LTK2QIF5
Calibration-Free Gas Source Localization with Mobile Robots: Source Term Estimation Based on Concentration Measurement Ranking
Relative ranking of gas measurements lets robots localize sources without calibrating sensors.
arxiv:2605.13208 v1 · 2026-05-13 · cs.RO
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Claims
By comparing the rank differences between gathered and modeled values, we estimate the probabilistic distribution of source locations across the entire environment. We validate our approach in high-fidelity simulations and physical experiments, demonstrating consistent localization accuracy with uncalibrated gas sensors.
That relative ranking of gas measurements within the dynamically accumulated dataset preserves enough information to distinguish source locations despite nonlinear sensor responses, environmental disturbances, and robot motion.
A ranking-based algorithm enables calibration-free probabilistic gas source localization by matching relative orders of measured and modeled concentrations.
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| First computed | 2026-05-18T03:08:48.573467Z |
|---|---|
| Builder | pith-number-builder-2026-05-17-v1 |
| Signature | Pith Ed25519
(pith-v1-2026-05) · public key |
| Schema | pith-number/v1.0 |
Canonical hash
5cd5a820bda27b95276723129de1472a9cd9ac8783d1c2d0fbf7a70463d76a3e
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· · · · ·Agent API
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curl -sH 'Accept: application/ld+json' https://pith.science/pith/LTK2QIF5UJ5ZKJ3HEMJJ3YKHFK \
| 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())"
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Canonical record JSON
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