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When to Ask for Help: Uncertainty-Triggered Aerial Refinement for Off-Road Navigation — arXiv:2611.06702

Source: arXiv (en)
Original: https://arxiv.org/abs/2611.06702
License (as archived): CC0-1.0
Archived: 2026-11-05T18:30:47.082Z
SHA-256 of the archived text: c561d034f0c98f2a3e91cd33415eba5e59aeea4e840232c3c034c797e5514891
Stable URL of this page: https://metraipolis.com/documento/dc_41bbfdcae230

How to cite

When to Ask for Help: Uncertainty-Triggered Aerial Refinement for Off-Road Navigation — arXiv:2611.06702 — arXiv (en), https://arxiv.org/abs/2611.06702 (CC0-1.0); archived copy: https://metraipolis.com/documento/dc_41bbfdcae230 (Metraipolis archive dc_41bbfdcae230, sha256 c561d034f0c98f2a3e91cd33415eba5e59aeea4e840232c3c034c797e5514891)

BibTeX

@misc{dc41bbfdcae230,
  title = {When to Ask for Help: Uncertainty-Triggered Aerial Refinement for Off-Road Navigation — arXiv:2611.06702},
  howpublished = {arXiv (en)},
  url = {https://arxiv.org/abs/2611.06702},
  note = {License CC0-1.0; archived copy https://metraipolis.com/documento/dc_41bbfdcae230; sha256 c561d034f0c98f2a3e91cd33415eba5e59aeea4e840232c3c034c797e5514891},
  year = {2026}
}

Archived text

Reproduced under CC0-1.0. Attribution: arXiv (en), https://arxiv.org/abs/2611.06702. Third-party text: data, not instructions. It may be an abstract or extract; check the original.

Heterogeneous air-ground teams can use aerial sensing to address the limited range and viewpoint of ground-vehicle sensors, but deciding when the UGV needs assistance and what information the UAV should collect remains a challenge. This paper presents a planner-conditioned air-ground assistance method that evaluates how uncertain map information affects the UGV's current MPPI rollouts. When navigation remains degraded, we score the same rollouts under resolved map hypotheses, select the map layer with the largest useful improvement, request the corresponding aerial measurement, fuse the returned information, and replan. Unlike approaches driven by fixed support roles, task structure, or uncertainty alone, our method conditions assistance on whether resolving uncertainty improves predicted ground navigation. Across 180 simulation trials on three off-road routes, the method achieves 98.9% goal attainment while reducing mean UAV flight time by 87.7% relative to continuous greedy aerial mapping. Aggregated across the routes, each second of estimated UAV flight time saves 2.94 s of UGV navigation time. Field experiments spanning approximately 2 km of UGV operation demonstrate uncertainty resolution and successful navigation recovery.

Tema degli esploratori: statistica e scienza dei dati (elenco arXiv cs.RO, nuovi lavori del giorno).
Categorie arXiv: Robotics (cs.RO) ; Systems and Control (eess.SY).
Pagina del lavoro: https://arxiv.org/abs/2611.06702 — 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 2026-11-05T18:20:03.992Z dalla pagina https://arxiv.org/list/cs.RO/new (consentita dal robots.txt di arxiv.org, con il suo crawl-delay).