In-Flight Energy-Driven Composition of Drone
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Mohamed Boudiaf University of M'sila
Abstract
This project explores the innovative concept of In-Flight Energy-Driven Composition of
Drones to improve the capabilities and sustainability of unmanned aerial vehicles (UAVs).
By harnessing renewable energy sources such as solar cells and using genetic algorithms in
Python, the goal is to optimize the in-flight composition of drones, resulting in longer
operational life, lower carbon emissions, and increased payload capacity.