LATIDIA · Robótica

OntoPlan: una representación de escena basada en ontología y un marco agénico para la planificación escalable de tareas de robots

arXiv: 2610.07649v1Tipo de anuncio: nuevo Resumen: la planificación de tareas robóticas basada en el modelo de lenguaje grande (LLM) es prometedora para el seguimiento de instrucciones abiertas, pero se degrada en tareas de horizonte largo en entornos grandes. Cuando es espacioso

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arXiv:2610.07649v1 Announce Type: new Abstract: Large language model (LLM)-based robot task planning is promising for open-ended instruction following, but degrades on long-horizon tasks in large environments. When spatial information is conveyed to the LLM through text, the model can fail to capture spatial context, and token cost grows with environment size. Generating action sequences directly with an LLM also makes it difficult to satisfy the current world state and action preconditions. We address this with an ontology-grounded scene representation that aligns objects, spaces, relations, and states in a shared symbolic vocabulary for spatial reasoning and task planning, and with OntoPlan, an agentic framework that interprets instructions, selectively retrieves task-relevant information,