Home  /  Mundo Fesc  /  Vol: 9 Núm: 18 Par: 0 (2019)  /  Article
ARTICLE
TITLE

Técnicas de slam con filtros probabilísticos: caracterización y resultados en robots móviles

SUMMARY

El desafío de la localización y mapeo SLAM (Simultaneous Localization And Mapping) en robots móviles consiste en descubrir si es posible navegar a través de un entorno desconocido y construir de manera incremental un mapa consistente del mismo, mientras que determina al mismo tiempo su posición dentro del mapa. La solución teórico-conceptual ha sido desarrollado por el SLAM especialmente con filtros de localización, tales como: el filtro de Kalman, el filtro de información, el filtro gráfico y el filtro de partículas entre otros. El estudio realizado al variar marcas establecidas en las trayectorias y analizar estos filtros desde el punto de vista probabilístico que se encuentran incorporados en dos prototipos de robots móviles que poseen sensores de ultrasonido y láser, muestra resultados de errores en odometría y tiempos necesarios que cada filtro SLAM tiene en promedio por iteración para la construcción del mapa bidimensional. Palabras clave: Filtro de Kalman, localización, robot móvil, sensor, SLAM.

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