LATIDIA · Robótica

Explicabilidad del modelo de lenguaje grande para planificar trayectorias de rover lunar bajo incertidumbre

arXiv: 2611.13292v1Tipo de anuncio: nuevo Resumen: La planificación de las trayectorias del rover planetario bajo incertidumbre probabilística es un problema de optimización multiobjetivo que los equipos científicos actualmente resuelven y verifican iterativamente

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arXiv:2611.13292v1 Announce Type: new Abstract: Planning planetary rover trajectories under probabilistic uncertainty is a multi-objective optimization problem that science teams currently iteratively solve and verify by hand. This process becomes impractical when timelines and constraints frequently shift throughout the mission planning phase. Sampling-based planners such as Monte Carlo tree search can speed up this process, but their outputs do not preserve traceability to the science objectives that justify each plan, which the science team needs to verify. We propose an interactive assistant based on a large language model (LLM) that can explain planner trajectories using domain vocabulary and re-run the planner under user-specified conditions to compare alternatives. Previous work has