LATIDIA · Robótica

Loco-manipulación planar guiada por LLM para robots cuadrúpedos

arXiv:2610.40248v1 Tipo de anuncio: nuevo Resumen: La navegación robótica generalmente asume que existe una ruta libre de colisiones hacia la meta; en entornos desordenados con obstáculos móviles, sin embargo, alcanzar la meta puede requerir

La noticia

arXiv:2610.40248v1 Announce Type: new Abstract: Robotic navigation typically assumes a collision-free route to the goal exists; in cluttered environments with movable obstacles, however, reaching the goal may require physical interaction. Classical solutions encode these behaviors through geometric rules and task-specific logic, while learning-based approaches often constrain the decision space to low-dimensional motion commands or predefined action sets. We instead consider a broader decision space, jointly selecting the skill, relevant object, and geometric target. Our language-conditioned task planner, fine-tuned with LoRA on synthetic data, maps natural-language tasks and a structured scene representation to variable-length sequences of parameterized actions, executed by low-level reinforcement-learning policies. The planner learns the geometric relations underlying interactive