Formación de Recurso Humano para la Ctel: Proyecto ejecutado con investigadores en empresas, industrias y Estado
Desarrollo de un algoritmo de navegación autónoma para uavs basado en objetivos dados usando técnicas de aprendizaje por refuerzo profundo
Fecha
2019-08Autor
Calderon Chavez, Juan Manuel
Guarnizo Marín, José Guillermo
Institución
Resumen
Natural disasters and wars are some of the worst events that the
humanity has had to face, since in this type of situation it is almost impossible
evacuate people in the affected area, causing many more deaths and an impact
devastating. Therefore, it is necessary to use autonomous robots that collaborate
in the search and rescue of human victims in disaster areas. This project of
research proposes the use of deep reinforcement learning techniques or "Deep
Reinforcement Lerning - DRL "to provide navigation skills
autonomous and adaptation in unknown environments to an unmanned aerial robot. I know
proposes the use of visual information as a sensing system for the environment. Given the
the environment is unstructured and unknown to the robotic agent will not be built
maps nor will any attempt be made to strictly follow a map. Navigation is based on the
follow-up and evasion of given objectives, which include people,
trees, fire and other objects that are considerably identifiable by
visual information in a disaster area.