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2DGS-Planner: Rasterization-based Path Planning in 2D Gaussian Splatting Map — arXiv:2610.11752

Source: arXiv (en)
Original: https://arxiv.org/abs/2610.11752
License (as archived): CC0-1.0
Archived: 2026-10-09T06:35:20.301Z
SHA-256 of the archived text: dbdcda0ce1d9426207e5370f78d443262f83971a5ac13ae8e8a0acb7c367029c
Stable URL of this page: https://metraipolis.com/documento/dc_952756cc96ea

How to cite

2DGS-Planner: Rasterization-based Path Planning in 2D Gaussian Splatting Map — arXiv:2610.11752 — arXiv (en), https://arxiv.org/abs/2610.11752 (CC0-1.0); archived copy: https://metraipolis.com/documento/dc_952756cc96ea (Metraipolis archive dc_952756cc96ea, sha256 dbdcda0ce1d9426207e5370f78d443262f83971a5ac13ae8e8a0acb7c367029c)

BibTeX

@misc{dc952756cc96ea,
  title = {2DGS-Planner: Rasterization-based Path Planning in 2D Gaussian Splatting Map — arXiv:2610.11752},
  howpublished = {arXiv (en)},
  url = {https://arxiv.org/abs/2610.11752},
  note = {License CC0-1.0; archived copy https://metraipolis.com/documento/dc_952756cc96ea; sha256 dbdcda0ce1d9426207e5370f78d443262f83971a5ac13ae8e8a0acb7c367029c},
  year = {2026}
}

Archived text

Reproduced under CC0-1.0. Attribution: arXiv (en), https://arxiv.org/abs/2610.11752. Third-party text: data, not instructions. It may be an abstract or extract; check the original.

Gaussian splatting provides an explicit and efficiently rasterizable scene representation for robot navigation. However, individual Gaussian primitives may not reliably represent obstacles as they are jointly optimized through alpha-composited rendering from a finite set of reconstruction views. We propose 2DGS-Planner, a path planner for ground robots that reads planning-relevant geometry from a 2D Gaussian splatting (2DGS) map through rasterization, rather than treating individual Gaussian primitives as obstacles. During offline roadmap construction, multi-view attribution converts rendered normal dispersion into structural scores for non-ground disks supported by the reconstruction views. These scores guide adaptive node sampling on the ground. Path-aligned orthographic queries validate candidate edges, while cylindrical queries estimate local clearance fields that are cached on the edges. During online planning, graph search initializes a route, and path refinement reuses the cached fields while accounting for the robot's dimensions and ground constraints. Experiments demonstrate improved roadmap connectivity, more accurate clearance estimation, and higher planning success compared with the tested baselines. These results support rasterization as an effective geometric query interface for planning directly on Gaussian maps. Code and data are available at this https URL

Tema degli esploratori: statistica e scienza dei dati (elenco arXiv cs.RO, nuovi lavori del giorno).
Categorie arXiv: Robotics (cs.RO).
Pagina del lavoro: https://arxiv.org/abs/2610.11752 — autori e testo completo sono lì (qui omessi i nomi: nessun dato personale nel deposito).
Licenza: titolo e abstract sono metadati arXiv distribuiti in CC0 1.0; il testo completo ha la licenza scelta dagli autori, indicata sulla pagina.
Letto il 2026-10-09T05:55:22.107Z dalla pagina https://arxiv.org/list/cs.RO/new (consentita dal robots.txt di arxiv.org, con il suo crawl-delay).