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A Biophysically Detailed C. elegans Circuit as a Task-Agnostic Dynamical Core for Visually Robust Robot Manipulation — arXiv:2609.39322

Source: arXiv (en)
Original: https://arxiv.org/abs/2609.39322
License (as archived): CC0-1.0
Archived: 2026-10-07T15:12:01.186Z
SHA-256 of the archived text: 0bf9a4c6964d5d34610a88fc81d129789b0c49de2ac85faf3c90f216f94394ae
Stable URL of this page: https://metraipolis.com/documento/dc_ae8dfd02d2fd

How to cite

A Biophysically Detailed C. elegans Circuit as a Task-Agnostic Dynamical Core for Visually Robust Robot Manipulation — arXiv:2609.39322 — arXiv (en), https://arxiv.org/abs/2609.39322 (CC0-1.0); archived copy: https://metraipolis.com/documento/dc_ae8dfd02d2fd (Metraipolis archive dc_ae8dfd02d2fd, sha256 0bf9a4c6964d5d34610a88fc81d129789b0c49de2ac85faf3c90f216f94394ae)

BibTeX

@misc{dcae8dfd02d2fd,
  title = {A Biophysically Detailed C. elegans Circuit as a Task-Agnostic Dynamical Core for Visually Robust Robot Manipulation — arXiv:2609.39322},
  howpublished = {arXiv (en)},
  url = {https://arxiv.org/abs/2609.39322},
  note = {License CC0-1.0; archived copy https://metraipolis.com/documento/dc_ae8dfd02d2fd; sha256 0bf9a4c6964d5d34610a88fc81d129789b0c49de2ac85faf3c90f216f94394ae},
  year = {2026}
}

Archived text

Reproduced under CC0-1.0. Attribution: arXiv (en), https://arxiv.org/abs/2609.39322. Third-party text: data, not instructions. It may be an abstract or extract; check the original.

Robot policies are usually trained for one task, one body and one visual environment, and generalize poorly beyond these conditions. Whether a nervous system can instead supply the sensorimotor computation through its evolved wiring and biophysics remains unresolved. Here we embed a biophysically detailed Caenorhabditis elegans sensorimotor circuit - 136 multicompartment neurons with realistic morphologies and electrophysiological characteristics - as the dynamical core of a visuomotor policy. Only thin task-specific adapters are trained; the core's synaptic weights stay fixed while its membrane voltages evolve freely. Across different MetaWorld tasks the core matches or exceeds diffusion-policy, action-chunking-transformer and neural-circuit-policy baselines, and degrades less under visual perturbations. Replacing the core with generic network models such as MLP, LSTM, transformer or reservoir networks removes the advantage. Furthermore, on a real robotic arm the core withstands diverse visual perturbations that collapse the baselines. Our results suggest that visual robustness can be inherited from biophysically detailed circuit dynamics rather than learned by task-specific controllers.

Tema degli esploratori: statistica e scienza dei dati (retro-catalogo arXiv: annunci del 2026-10-01 in cs.RO).
Categorie arXiv: Robotics (cs.RO).
Pagina del lavoro: https://arxiv.org/abs/2609.39322 — 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 2026-10-07T14:44:47.436Z dalla pagina https://arxiv.org/catchup/cs.RO/2026-10-01?abs=True (consentita dal robots.txt di arxiv.org, con il suo crawl-delay).