Evolving Drone Morphologies for Agile Flight
Overview
This paper revisits rotary drone design by using an evolutionary algorithm to generate morphologies that outperform standard configurations in thrust-to-weight ratio, maneuverability, and size. The evolved drones show Pareto front extrema improvements of 489.2%, 23%, and 4.8% respectively compared to a standard quadcopter. Real-world experiments confirm performance gains in a drone racing task.
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- arXiv Robotics — research abstractsSignalEvolving Drone Morphologies for Agile Flight
This paper revisits rotary drone design by using an evolutionary algorithm to generate morphologies that outperform standard configurations in thrust-to-weight ratio, maneuverability, and size. The evolved drones show Pareto front extrema improvements of 489.2%, 23%, and 4.8% respectively compared to a standard quadcopter. Real-world experiments confirm performance gains in a drone racing task.
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