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UniTrackPLA: Unified Panorama-Language-Action Model for Instruction-Guided Navigation and Dynamic Person Tracking — arXiv:2610.00878

Source: arXiv (en)
Original: https://arxiv.org/abs/2610.00878
License (as archived): CC0-1.0
Archived: 2026-10-06T19:16:33.727Z
SHA-256 of the archived text: a75c48777695f88d95dda2efd4237c42878f8e87f4cac39dfc0362f91dfccb4a
Stable URL of this page: https://metraipolis.com/documento/dc_03b9b00aee69

How to cite

UniTrackPLA: Unified Panorama-Language-Action Model for Instruction-Guided Navigation and Dynamic Person Tracking — arXiv:2610.00878 — arXiv (en), https://arxiv.org/abs/2610.00878 (CC0-1.0); archived copy: https://metraipolis.com/documento/dc_03b9b00aee69 (Metraipolis archive dc_03b9b00aee69, sha256 a75c48777695f88d95dda2efd4237c42878f8e87f4cac39dfc0362f91dfccb4a)

BibTeX

@misc{dc03b9b00aee69,
  title = {UniTrackPLA: Unified Panorama-Language-Action Model for Instruction-Guided Navigation and Dynamic Person Tracking — arXiv:2610.00878},
  howpublished = {arXiv (en)},
  url = {https://arxiv.org/abs/2610.00878},
  note = {License CC0-1.0; archived copy https://metraipolis.com/documento/dc_03b9b00aee69; sha256 a75c48777695f88d95dda2efd4237c42878f8e87f4cac39dfc0362f91dfccb4a},
  year = {2026}
}

Archived text

Reproduced under CC0-1.0. Attribution: arXiv (en), https://arxiv.org/abs/2610.00878. Third-party text: data, not instructions. It may be an abstract or extract; check the original.

General-purpose embodied robots should support both navigation toward language-specified destinations and dynamic person tracking under arbitrary initial target azimuths. However, existing methods typically rely on forward-facing observations and address these tasks with separate policies, limiting omnidirectional perception and unified closed-loop control. We present UniTrackPLA, a unified panorama-language-action model for instruction-guided navigation and dynamic person tracking. Its Panoramic-Aware Encoding (PAE) preserves the temporal and azimuthal structure of perspective views projected from each panorama, enabling perspective-pretrained visual encoders to process omnidirectional observations. A shared vision-language backbone grounds instructions in the panoramic context and predicts continuous robot-centric waypoint chunks for both tasks. World-Action Consistency (WAC) further predicts action-conditioned future visual states and verifies waypoint prefixes online, allowing reliable actions to be reused while triggering replanning upon inconsistency. We also introduce OmniTrackNav-Bench, comprising 5,000 simulated tracking trajectories, 10,000 simulated VLN routes, and 96 verified real-world routes, providing 919,978 waypoint-supervision instances. UniTrackPLA improves overall tracking SR from 23.50% to 35.00% and Omni-VLN SR/SPL from 13.00%/12.77% to 19.75%/19.29%. Incorporating 76 real-world routes further improves held-out [email protected] from 42.92% to 92.08%. Closed-loop experiments on a Go2-W robot demonstrate unified panoramic tracking and navigation across indoor and outdoor environments. The project page is at this https URL .

Tema degli esploratori: statistica e scienza dei dati (retro-catalogo arXiv: annunci del 2026-10-02 in cs.CV).
Categorie arXiv: Robotics (cs.RO) ; Computer Vision and Pattern Recognition (cs.CV); Image and Video Processing (eess.IV).
Pagina del lavoro: https://arxiv.org/abs/2610.00878 — 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 2026-10-06T17:37:36.935Z dalla pagina https://arxiv.org/catchup/cs.CV/2026-10-02?abs=True (consentita dal robots.txt di arxiv.org, con il suo crawl-delay).