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Ludi${}_{\scriptscriptstyle 0.1}$: An Agentic System for Socially Intelligent Robots — arXiv:2608.22035

Source: arXiv (en)
Original: https://arxiv.org/abs/2608.22035
License (as archived): CC0-1.0
Archived: 2026-10-18T09:02:04.115Z
SHA-256 of the archived text: 1ad5afb53652c98f2ae2bdbcdf1a37041a909de540decefaa9c9541a92f07be6
Stable URL of this page: https://metraipolis.com/documento/dc_5b292ce45be2

How to cite

Ludi${}_{\scriptscriptstyle 0.1}$: An Agentic System for Socially Intelligent Robots — arXiv:2608.22035 — arXiv (en), https://arxiv.org/abs/2608.22035 (CC0-1.0); archived copy: https://metraipolis.com/documento/dc_5b292ce45be2 (Metraipolis archive dc_5b292ce45be2, sha256 1ad5afb53652c98f2ae2bdbcdf1a37041a909de540decefaa9c9541a92f07be6)

BibTeX

@misc{dc5b292ce45be2,
  title = {Ludi$_scriptscriptstyle 0.1$: An Agentic System for Socially Intelligent Robots — arXiv:2608.22035},
  howpublished = {arXiv (en)},
  url = {https://arxiv.org/abs/2608.22035},
  note = {License CC0-1.0; archived copy https://metraipolis.com/documento/dc_5b292ce45be2; sha256 1ad5afb53652c98f2ae2bdbcdf1a37041a909de540decefaa9c9541a92f07be6},
  year = {2026}
}

Archived text

Reproduced under CC0-1.0. Attribution: arXiv (en), https://arxiv.org/abs/2608.22035. Third-party text: data, not instructions. It may be an abstract or extract; check the original.

Robot foundation models have substantially advanced perception and control, but natural human-robot collaboration requires more than executing isolated commands. A robot must recognize ambiguity, maintain context across turns, communicate its intentions, and revise ongoing behavior as the user's intent changes. We present $\scriptstyle\mathsf{Ludi}_{\scriptscriptstyle 0.1}$, an agentic system for socially intelligent robots that integrates interactive speech, multimodal reasoning, memory, navigation, and learned manipulation. Its decision-making core is a fine-tuned vision-language model trained on multi-turn interaction traces spanning ambiguous requests, clarifications, corrections, interruptions, mixed social and task dialogue, and multi-step tasks. A purpose-built harness manages the model-tool interaction loop, while specialized navigation and manipulation policies execute physical skills. Ludi${}_{\scriptscriptstyle 0.1}$ demonstrates a practical path toward fluid human-robot collaboration today while producing the multimodal interaction traces needed to develop a more deeply integrated foundation model for robots and people.

Tema degli esploratori: statistica e scienza dei dati (retro-catalogo arXiv: annunci del 2026-08-25 in cs.RO).
Categorie arXiv: Robotics (cs.RO).
Pagina del lavoro: https://arxiv.org/abs/2608.22035 — 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 2026-10-18T08:57:47.850Z dalla pagina https://arxiv.org/catchup/cs.RO/2026-08-25?abs=True (consentita dal robots.txt di arxiv.org, con il suo crawl-delay).