Giovanni Sanna
Neural Network Based Algorithm for Multi-UAV Coverage Path Planning.
Rel. Giorgio Guglieri, Simone Godio. Politecnico di Torino, Corso di laurea magistrale in Ingegneria Aerospaziale, 2021
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Abstract
Unmanned Aerial Vehicles, better known as drones, have become an eye in the sky to aid men with a perspective from above. They provide real-time, high-resolution imagery at low cost. Originally thought for military applications, UAVs have found their way into mainstream usage thanks to the enhanced levels of safety and efficiency they bring. Robotic UAVs operate without an onboard pilot; the trend is of continuous evolution with an ever increasing level of automation. On the other side, Artificial Neural Networks lead the cutting-edge machine learning techniques, whose purpose is to render machines more and more intelligent by means of bio-inspired models.
This work combines both the potential of artificial intelligence with drone-based surveillance capabilities - a fleet of AI-driven UAVs executes the Coverage Path Planning of a complex-shaped urban areas
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