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Aplicación de técnicas de aprendizaje por refuerzo a navegación visual

Authors: Pina Navarro, Mónica;

Aplicación de técnicas de aprendizaje por refuerzo a navegación visual

Abstract

En los últimos años, tanto el número de accidentes de tráfico como de víctimas mortales ha ido en aumento. De todos estos accidentes únicamente un 10% fueron a causa del mal estado del vehículo o de la vía. En cambio, el otro 90% restante fue por factor humano. Aunque, en un principio, puede parecer sencillo evitar esta fatalidad, la realidad es que cuanto más se conduce, más falsa sensación de seguridad se adquiere. Cada vez más vehículos, han ido incorporando nuevos elementos de seguridad activa para la prevención de los accidentes. Aunque todas estas nuevas tecnologías pueden evitar situaciones peligrosas, resultan insuficientes. Por eso, la automatización puede llegar a ser una gran solución para ayudar a reducir el número de accidentes en carreteras. La finalidad inicial de esta investigación es la de lograr que un robot móvil, en este caso TurtleBot, mediante un algoritmo de RL, más concretamente Gradiente de política determinista profundo (DDPG), sea capaz de seguir una línea dibujada en el suelo sin necesidad de intervención humana. Para ello, se implementará el algoritmo de RL para un entorno simulado tridimensional en el software Gazebo. Una vez ahí, se procederá a trasladar lo anterior al robot real, de manera que, para un escenario desconocido, el robot TurtleBot sea capaz de circular sin salirle de la línea amarilla configurada.

Keywords

Navegación visual, Aprendizaje por refuerzo, Robótica móvil, TurtleBot, Ciencia de la Computación e Inteligencia Artificial

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
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