arXiv: cs.AI preprintsInternational11 November 2026
Taxonomy-Agnostic Neurosymbolic Grounding of Robot Kinematics
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arXiv:2611.13850v1 Announce Type: new Abstract: While symbolic reasoning for task allocation requires grounding a robot's physical capabilities, standard Unified Robot Description Format (URDF) files provide only low-level kinematics without the formal semantic context needed for reasoning. We present URDF2Ontology, an automated, taxonomy-agnostic neurosymbolic framework that transforms raw URDF files into populated, grounded OWL ontologies. It leverages a Large Language Model (LLM) for targeted semantic reasoning, coupled with an iterative sequential graph-purging mechanism to prevent context
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