LATIDIA · Robótica

Planificación asistida por LLM con ejecución distribuida del árbol de comportamiento a bordo para misiones multi-AUV

arXiv: 2611.04518v1Tipo de Anuncio: nuevo Resumen: Coordinar vehículos submarinos autónomos requiere traducir la intención del operador en asignaciones factibles mientras se preserva la ejecución autónoma cuando la comunicación es limitada

La noticia

arXiv:2611.04518v1 Announce Type: new Abstract: Coordinating autonomous underwater vehicles requires translating operator intent into feasible assignments while preserving autonomous execution when communication is limited. We present a hierarchical framework that couples Large Language Model (LLM) interpretation of natural-language mission instructions with Mixed-Integer Linear Programming (MILP) and distributed Behaviour Tree (BT) execution. The LLM extracts assignment and ordering constraints, which the MILP optimizer combines with vehicle capabilities and temporal requirements. A BT-LLM Bridge distributes the resulting allocations to onboard BT Mission Managers. Per-vehicle Robotic Agents assess local faults and request selective replanning, allowing unaffected vehicles to continue their assigned tasks. Evaluation in a ROS-based AUV simulator compares Qwen-3-8B and Llama-3.1-8B on