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pith:TTB3YLVA

pith:2026:TTB3YLVAY4ZSSDGTS46KEL5UDF

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Asymptotically Optimal Ergodic Coverage on Generalized Motion Fields

Christian Hughes, Darrick Lee, Fabio Ramos, Houston Warren, Ian Abraham, Julia Engdahl, Travis Miles, Yanis Lahrach, Yilang Liu

A flow-adaptive MMD formulation preserves ergodic coverage guarantees in time-varying domains and supports under-actuated open-loop robot planning.

arxiv:2605.13442 v1 · 2026-05-13 · cs.RO

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Claims

C1strongest claim

We show that this approach preserves ergodic coverage guarantees in ambient flows and enables effective exploration in under-actuated, and even open-loop planning settings by integrating environment dynamics.

C2weakest assumption

That the flow fields and domain evolution are known or accurately modeled in advance so the adaptive MMD objective can be computed and optimized without feedback.

C3one line summary

A flow-adaptive ergodic coverage formulation using MMD that preserves guarantees over evolving domains and supports open-loop planning for robots in flows.

References

49 extracted · 49 resolved · 0 Pith anchors

[1] Ian Abraham, Ahalya Prabhakar, and Todd D. Mur- phey. Active area coverage from equilibrium. In Marco Morales, Lydia Tapia, Gildardo S ´anchez-Ante, and Seth Hutchinson, editors,Algorithmic Foundation 2020

[2] An information-based exploration strategy for environ- ment mapping with mobile robots.Robotics and Autonomous Systems, 58(5):684–699, 2010 2010 · doi:10.1016/j.robot.2009.11

[3] URL https://www.sciencedirect.com/science/article/ pii/S0921889009002024

[4] Information based adaptive robotic exploration 2002

[5] Rik B ¨ahnemann, Nicholas Lawrance, Jen Jen Chung, Michael Pantic, Roland Siegwart, and Juan Nieto.Re- visiting Boustrophedon Coverage Path Planning as a Generalized Traveling Salesman Problem, page 2 2021 · doi:10.1007/978-981-15-9460-1

Receipt and verification

First computed	2026-05-18T02:44:42.077435Z
Builder	pith-number-builder-2026-05-17-v1
Signature	Pith Ed25519 (`pith-v1-2026-05`) · public key
Schema	pith-number/v1.0

Canonical hash

9cc3bc2ea0c733290cd3973ca22fb41943256940ea4ded70789d4d3c8277fa88

Aliases

arxiv: 2605.13442 · arxiv_version: 2605.13442v1 · doi: 10.48550/arxiv.2605.13442 · pith_short_12: TTB3YLVAY4ZS · pith_short_16: TTB3YLVAY4ZSSDGT · pith_short_8: TTB3YLVA

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Verify this Pith Number yourself

curl -sH 'Accept: application/ld+json' https://pith.science/pith/TTB3YLVAY4ZSSDGTS46KEL5UDF \
  | 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: 9cc3bc2ea0c733290cd3973ca22fb41943256940ea4ded70789d4d3c8277fa88

Canonical record JSON

{
  "metadata": {
    "abstract_canon_sha256": "9387d2d3227c92dbad32028026b6792e5f00341c754fc002a3a8a66aa7774aeb",
    "cross_cats_sorted": [],
    "license": "http://creativecommons.org/licenses/by-nc-nd/4.0/",
    "primary_cat": "cs.RO",
    "submitted_at": "2026-05-13T12:37:27Z",
    "title_canon_sha256": "fd9e659bbbeb522ffa1d407f8a2c329e4e67b39792678f0a5354fb23e34728ce"
  },
  "schema_version": "1.0",
  "source": {
    "id": "2605.13442",
    "kind": "arxiv",
    "version": 1
  }
}