{"about":{"site":"https://codewithpapers.app","non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page"},"url":"/paper/from-vocal-instructions-to-household-tasks","title":"From Vocal Instructions to Household Tasks: The Inria Tiago++ in the euROBIN Service Robots Coopetition","arxiv_id":"2412.17861","date":"2024-12-20","proceeding":null,"authors":["Fabio Amadio","Clemente Donoso","Dionis Totsila","Raphael Lorenzo","Quentin Rouxel","Olivier Rochel","Enrico Mingo Hoffman","Jean-Baptiste Mouret","Serena Ivaldi"],"abstract":"This paper describes the Inria team's integrated robotics system used in the 1st euROBIN coopetition, during which service robots performed voice-activated household tasks in a kitchen setting. The team developed a modified TIAGo++ platform that leverages a whole-body control stack for autonomous and teleoperated modes, and an LLM-based pipeline for instruction understanding and task planning. The key contributions (opens-sourced) are the integration of these components and the design of custom teleoperation devices, addressing practical challenges in the deployment of service robots.","url_abs":"https://arxiv.org/abs/2412.17861v1","url_pdf":"https://arxiv.org/pdf/2412.17861v1.pdf","source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","row_kind":"links_only","authors_date_abstract":"arXiv metadata, CC0 1.0 (https://info.arxiv.org/help/license), from the Kaggle arXiv metadata snapshot of 2026-09-12"},"code_links":[{"paper_slug":"from-vocal-instructions-to-household-tasks","repo_url":"https://github.com/hucebot/eurobin_llm_plan","is_official":1,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"pytorch","reach":null}],"tasks":[],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"syntology_url":null,"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}