Metraipolis › archive › dc_34bb698a997d

Retrieval-grounded robot program generation and simulation-based correction via Model Context Protocol — arXiv:2608.21417

Source: arXiv (en)
Original: https://arxiv.org/abs/2608.21417
License (as archived): CC0-1.0
Archived: 2026-10-18T07:38:39.644Z
SHA-256 of the archived text: e6cee99b0ac41f65d299dc09a91eedb71a3872d98f09fe4a06ece480c80a9897
Stable URL of this page: https://metraipolis.com/documento/dc_34bb698a997d

How to cite

Retrieval-grounded robot program generation and simulation-based correction via Model Context Protocol — arXiv:2608.21417 — arXiv (en), https://arxiv.org/abs/2608.21417 (CC0-1.0); archived copy: https://metraipolis.com/documento/dc_34bb698a997d (Metraipolis archive dc_34bb698a997d, sha256 e6cee99b0ac41f65d299dc09a91eedb71a3872d98f09fe4a06ece480c80a9897)

BibTeX

@misc{dc34bb698a997d,
  title = {Retrieval-grounded robot program generation and simulation-based correction via Model Context Protocol — arXiv:2608.21417},
  howpublished = {arXiv (en)},
  url = {https://arxiv.org/abs/2608.21417},
  note = {License CC0-1.0; archived copy https://metraipolis.com/documento/dc_34bb698a997d; sha256 e6cee99b0ac41f65d299dc09a91eedb71a3872d98f09fe4a06ece480c80a9897},
  year = {2026}
}

Archived text

Reproduced under CC0-1.0. Attribution: arXiv (en), https://arxiv.org/abs/2608.21417. Third-party text: data, not instructions. It may be an abstract or extract; check the original.

Flexible manufacturing requires industrial robots to be reprogrammed rapidly as product variants change. This paper presents a language-model-based workflow that generates, validates, and iteratively corrects ABB RAPID robot programs from natural language task descriptions. A dual-stream retrieval-augmented generation (RAG) pipeline grounds code generation in verified technical documentation and production templates, reducing domain-specific errors produced by ungrounded language models. A custom Model Context Protocol (MCP) server connects the language-model client directly to ABB RobotStudio for automated code upload, simulation execution, and diagnostic feedback. The evaluation combines a 30-query retrieval benchmark, scoped code-generation checks, and RobotStudio case studies in a simulated pickand- place manufacturing cell. The simulation loop exposes execution failures that static and semantic checks alone cannot catch, including suction release-height errors, unreachable placement targets, and configuration-dependent recovery motions. The results show how RAG and MCP can connect grounded code generation with executable feedback from industrial robot simulation software, while reducing but not eliminating expert setup and final supervision.

Tema degli esploratori: agenti e intelligenza artificiale (retro-catalogo arXiv: annunci del 2026-08-25 in cs.AI).
Categorie arXiv: Artificial Intelligence (cs.AI) ; Robotics (cs.RO).
Pagina del lavoro: https://arxiv.org/abs/2608.21417 — 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 2026-10-18T07:37:52.639Z dalla pagina https://arxiv.org/catchup/cs.AI/2026-08-25?abs=True (consentita dal robots.txt di arxiv.org, con il suo crawl-delay).