Pith Number

pith:5FFG5GLV

pith:2025:5FFG5GLVC2H2GNTD7LXAG43M6Q

not attested not anchored not stored refs resolved

OptMap: Geometric Map Distillation via Submodular Maximization

Brett T. Lopez, Christa S. Robison, David Thorne, Nathan Chan, Philip R. Osteen

OptMap distills large LiDAR streams into compact application-specific maps by maximizing a submodular reward function with polynomial-time near-optimal algorithms.

arxiv:2512.07775 v2 · 2025-12-08 · cs.RO

Open paper page JSON Open Graph Bundle Merged state Verified badge What is a Pith Number?

Add to your LaTeX paper

\usepackage{pith}
\pithnumber{5FFG5GLVC2H2GNTD7LXAG43M6Q}

Prints a linked badge after your title and injects PDF metadata. Compiles on arXiv. Learn more · Embed verified badge

Record completeness

1 Bitcoin timestamp

2 Internet Archive

3 Author claim open · sign in to claim

4 Citations open

5 Replications open

✓ Portable graph bundle live · download bundle · merged state

The bundle contains the canonical record plus signed events. A mirror can host it anywhere and recompute the same current state with the deterministic merge algorithm.

Claims

C1strongest claim

We present OptMap: a geometric map distillation algorithm which achieves online, application-specific map generation via multiple theoretical and algorithmic innovations. A central feature is the maximization of set functions that exhibit diminishing returns, i.e., submodularity, using polynomial-time algorithms with provably near-optimal solutions.

C2weakest assumption

That the proposed reward function is submodular (or sufficiently close) so that the polynomial-time greedy-style algorithms retain their near-optimality guarantees when applied to real LiDAR streams.

C3one line summary

OptMap generates compact, application-specific geometric maps from streaming LiDAR data using a novel submodular reward function and a dynamically reordered streaming maximization algorithm.

References

61 extracted · 61 resolved · 0 Pith anchors

[1] Overlaptransformer: An efficient and yaw-angle-invariant transformer network for lidar-based place recognition, 2022

[2] Overlapnet: A siamese network for computing lidar scan similarity with applications to loop closing and localization, 2022

[3] Padloc: Lidar-based deep loop closure detection and registration using panoptic attention, 2023

[4] Minkloc3d: Point cloud based large-scale place recog- nition, 2021

[5] Submodular optimization for keyframe selection & usage in slam, 2025

Formal links

2 machine-checked theorem links

Receipt and verification

First computed	2026-05-18T03:10:11.630696Z
Builder	pith-number-builder-2026-05-17-v1
Signature	Pith Ed25519 (`pith-v1-2026-05`) · public key
Schema	pith-number/v1.0

Canonical hash

e94a6e9975168fa33663faee03736cf4103a7974d33e162124c3617e838abaea

Aliases

arxiv: 2512.07775 · arxiv_version: 2512.07775v2 · doi: 10.48550/arxiv.2512.07775 · pith_short_12: 5FFG5GLVC2H2 · pith_short_16: 5FFG5GLVC2H2GNTD · pith_short_8: 5FFG5GLV

Agent API

Resolver JSON Graph JSON Events JSON Schema Signing key

Verify this Pith Number yourself

curl -sH 'Accept: application/ld+json' https://pith.science/pith/5FFG5GLVC2H2GNTD7LXAG43M6Q \
  | 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: e94a6e9975168fa33663faee03736cf4103a7974d33e162124c3617e838abaea

Canonical record JSON

{
  "metadata": {
    "abstract_canon_sha256": "f9ebe30c29aad80617b9b7baaab56fade7b9f9c8f186bff63110eee8802df2a8",
    "cross_cats_sorted": [],
    "license": "http://creativecommons.org/licenses/by/4.0/",
    "primary_cat": "cs.RO",
    "submitted_at": "2025-12-08T17:56:57Z",
    "title_canon_sha256": "8ef638ebb2dc2419d19b780aaf6b607d4750b95bdb0b84382054a3578b47cc9b"
  },
  "schema_version": "1.0",
  "source": {
    "id": "2512.07775",
    "kind": "arxiv",
    "version": 2
  }
}