LATIDIA · Robótica

USUARIO: Un sistema unificado y extensible para el aprendizaje de políticas en línea del mundo real en IA incorporada

arXiv:2602.07837v5 Tipo de anuncio: reemplazar Resumen: El aprendizaje de políticas en línea directamente en el mundo físico es una dirección prometedora pero desafiante para la inteligencia incorporada. A diferencia de la simulación, los sistemas del mundo real no pueden

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arXiv:2602.07837v5 Announce Type: replace Abstract: Online policy learning directly in the physical world is a promising yet challenging direction for embodied intelligence. Unlike simulation, real-world systems cannot be arbitrarily accelerated, cheaply reset, or massively replicated, suggesting that real-world policy learning is not merely an algorithmic problem, but inherently a systems problem. We present USER, a \underline{U}nified and extensible \underline{S}yst\underline{E}m for real-world online policy lea\underline{R}ning. On the systems side, USER introduces a hardware abstraction layer for unified robot management and an adaptive communication plane that enables efficient cloud-edge training. On the learning side, USER adopts a fully asynchronous training framework, designs a persistent and cache-aware replay buffer, and provides extensible abstractions