RODEOS — Robotic Data Ecosystem Semantic Model: Bridging Siloed Robot Systems

Kurzfassung

Industry robotics across automotive paint shops, pharmaceutical clean-rooms, and e-commerce warehouses still relies on bespoke data mappings: every new robot arrives with proprietary file formats, capability vocabularies, and safety descriptors, forcing engineering teams into multi-week manual integration cycles. To address this cost and agility gap, we introduce RODEOS—RObotic Data EcOsystem Semantic Model, an emerging, vendor-neutral semantic blueprint co-defined by a consortium of 24 industrial partners. RODEOS extends the W3C DCAT-3 core with robotics-specific classes for raw data, model assets, and executable services, while preserving the lightweight authoring demands voiced in interviews with 17 experts drawn from research institutes, industrial end-users, robotics and automation suppliers, system integrators, IT-infrastructure providers, and the machinery-industry association—thereby capturing a truly holistic cross-domain requirements profile. We conduct a qualitative ablation study comparing JSON schemas generated by an LLM with and without RODEOS schema constraints, finding that schema-guided generation improves precision, coverage, and consistency of the output. These contributions—(i) the RODEOS semantic model, (ii) an LLM-assisted authoring workflow, and (iii) initial empirical validation metrics—aim to accelerate robot-cell integration and lay the groundwork for a community-wide semantic robotics ecosystem.