Tecnología en Sistemas de Información

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Aplicación de Drones y Aprendizaje Reforzado en el Sistema de Envíos: Un Enfoque para Mejorar la Eficiencia en Rutas en Cali.
(Universidad Santiago de Cali, 2023-08-31) Zapateiro Carabali, Juan Diego; Cabezas Alzate, Diego Fernando
This work addresses the application of reinforcement learning in the route planning of a drone, for its implementation in delivery projects, commonly known as "delivery." It compares different current fixed-path methods and how this could enhance the flight performance of these devices, proposing the city of Cali as a use case scenario. A significant finding is observed through the development of this project, which results in a notable improvement in autonomously identifying various obstacles using the code developed within reinforcement learning environments. This advancement enables the machine, within a virtual environment, to determine the optimal route to reach the designated destination while navigating around obstacles. Considering that the city of Cali presents numerous obstacles that must be navigated during flight execution, the methodology and obtained results also highlight that reinforcement learning, when applied to delivery using drones, could be a suitable solution to optimize delivery times for various items. It can address challenges such as delivering different supplies or materials to hard-to-reach locations.