Detección de obstáculos y espacios transitables en entornos urbanos para sistemas de ayuda a la conducción basados en algoritmos de visión estéreo implementados en GPU

B. Musleh, A. de la Escalera, J.M. Armingol

Resumen

Tanto los sistemas avanzados de ayuda a la conducción (ADAS) aplicados a la mejora de la seguridad vial, como los sistemas de navegación autónoma de vehículos, demandan sensores y algoritmos cada vez más complejos, capaces de obtener e interpretar información del entorno vial. En concreto, las mayores dificultades surgen a la hora de analizar la información proveniente de los entornos urbanos, debido a la diversidad de elementos con distintas características que existen en áreas urbanas. Estos sistemas requieren, cada vez más, que la interpretación de la información se realice en tiempo real para mejorar la toma de decisiones. Por otra parte, la visión estéreo es ampliamente utilizada en sistemas de modelado, dada la gran cantidad de información que proporciona, pero al mismo tiempo, los algoritmos basados en esta técnica requieren de un elevado tiempo de cómputo que dificulta su implementación en aplicaciones de tiempo real. En este trabajo se presenta un algoritmo basado en visión estéreo para la detección tanto de obstáculos como de espacios transitables en entornos urbanos y que ha sido implementado principalmente en GPU (Unidad de Procesamiento Gráfico) para reducir el tiempo de cómputo y conseguir un funcionamiento en tiempo real.

Palabras clave

Visión por Computador; Vehículos Autónomos; Algoritmos de Detección; Sistemas de Tiempo Real

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