LATIDIA · Robótica

IA física para intralogística: evaluación comparativa del ecosistema Sim-to-Real de NVIDIA para la navegación de BRÚJULAS mejorada por el cosmos en robots móviles industriales

arXiv: 2610.28432v1Tipo de anuncio: nuevo Resumen: Las pilas de navegación de robots clásicos son confiables, pero a menudo requieren reingeniería para cada nuevo tipo de robot y sitio. La navegación basada en el aprendizaje desplaza este esfuerzo del ajuste manual

La noticia

arXiv:2610.28432v1 Announce Type: new Abstract: Classical robot navigation stacks are reliable but often require re-engineering for each new robot type and site. Learning-based navigation shifts this effort from hand-tuned parameters to data generation and training, where a policy adapts to each new embodiment or facility by fine-tuning in simulation. Whether policies adapted this way stay reliable on real industrial robots has seen little systematic testing. We study this for NVIDIA's X-Mobility and COMPASS workflow for training learned navigation policies on Idealworks robots. In simulation, we extend the COMPASS benchmark with two embodiments, the differential-drive iw.hub and an omnidirectional Humanoid Mobile Platform (HMP), and with a digital twin of the Idealworks