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META-Robot: Self-Cognition and Capability Scaling in Agentic Robots — arXiv:2610.41868

Source: arXiv (en)
Original: https://arxiv.org/abs/2610.41868
License (as archived): CC0-1.0
Archived: 2026-11-02T05:05:49.481Z
SHA-256 of the archived text: e285816104dbd5a4ae157560acce369550f1b811323bd7a46ce47485b9b7d7d6
Stable URL of this page: https://metraipolis.com/documento/dc_f7a8328811f4

How to cite

META-Robot: Self-Cognition and Capability Scaling in Agentic Robots — arXiv:2610.41868 — arXiv (en), https://arxiv.org/abs/2610.41868 (CC0-1.0); archived copy: https://metraipolis.com/documento/dc_f7a8328811f4 (Metraipolis archive dc_f7a8328811f4, sha256 e285816104dbd5a4ae157560acce369550f1b811323bd7a46ce47485b9b7d7d6)

BibTeX

@misc{dcf7a8328811f4,
  title = {META-Robot: Self-Cognition and Capability Scaling in Agentic Robots — arXiv:2610.41868},
  howpublished = {arXiv (en)},
  url = {https://arxiv.org/abs/2610.41868},
  note = {License CC0-1.0; archived copy https://metraipolis.com/documento/dc_f7a8328811f4; sha256 e285816104dbd5a4ae157560acce369550f1b811323bd7a46ce47485b9b7d7d6},
  year = {2026}
}

Archived text

Reproduced under CC0-1.0. Attribution: arXiv (en), https://arxiv.org/abs/2610.41868. Third-party text: data, not instructions. It may be an abstract or extract; check the original.

LLM-based robotic agent systems can generate programs for robot control, yet their generalization to new tasks often depends on elaborate scaffolding. Expanding their skill repertoires alone offers limited guidance on how to assess new capabilities or identify what remains beyond their reach. We introduce META-Robot, a framework that couples self cognition with capability scaling by expanding the criteria through which an agent evaluates and develops its skills. At its core, action-level predicates make execution outcomes explicit and available for LLM reasoning. The agent uses these assessments to identify its own limitations, extend relevant evaluation criteria, and guide the structured expansion of its skills. Proprioceptive feedback further grounds this process in the robot's physical state, enriching the evidence available for self-cognition. Experiments in simulation and on real robots demonstrate stronger overall task performance, generalization to new tasks, continued expansion of skills and evaluation criteria, and effective use of non-visual proprioceptive signals.

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/2610.41868 — 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 2026-11-02T04:49:28.231Z dalla pagina https://arxiv.org/list/cs.RO/new (consentita dal robots.txt di arxiv.org, con il suo crawl-delay).