Aerospace Engineering
Aerospace engineering is focused on designing, building, and operating aircraft and spacecraft, with current research heavily emphasizing autonomous systems and improved efficiency. Key areas of investigation include developing advanced control systems (e.g., using servo motors for improved rocket valve control), employing machine learning for tasks like visual inspection and predictive modeling (leveraging deep neural networks, Siamese networks, and Gaussian process regression), and creating robust, adaptive control algorithms for multi-robot cooperative transportation in diverse environments. These advancements aim to enhance safety, reduce costs, and improve the performance of aerospace systems.
Papers
A Systematic Study on Solving Aerospace Problems Using Metaheuristics
Carlos Alberto da Silva Junior, Marconi de Arruda Pereira, Angelo Passaro
Towards certification: A complete statistical validation pipeline for supervised learning in industry
Lucas Lacasa, Abel Pardo, Pablo Arbelo, Miguel Sánchez, Pablo Yeste, Noelia Bascones, Alejandro Martínez-Cava, Gonzalo Rubio, Ignacio Gómez, Eusebio Valero, Javier de Vicente