Dario Spiller

Agenzia Spaziale Italiana, Sapienza University of Rome

Papers

Total Citations

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About

Dario Spiller’s research lies at the intersection of autonomous space systems, real-time guidance, and artificial intelligence, with a focus on enabling safer and more efficient space missions. His major contributions include developing a Particle Swarm Optimization (PSO)-based guidance algorithm for soft lunar landing with hazard avoidance, a critical advancement for autonomous planetary exploration. This work, published in 2021 and garnering 11 citations, demonstrates how differential flatness can be combined with swarm intelligence to solve real-time optimal guidance problems. Spiller also pioneers hardware-in-the-loop (HIL) simulations for remote sensing disaster monitoring systems, integrating AI accelerators for on-board computation. His 2022 paper (4 citations) showcases how real-time image processing can support emergency response, while his 2023 work (3 citations) extends HIL simulations to future autonomous space systems. By bridging theoretical optimization with practical hardware validation, Spiller’s research directly addresses the challenges of real-time decision-making in resource-constrained space environments. His work is particularly notable for its emphasis on experimental validation, ensuring that algorithms are not just theoretically sound but also deployable in real missions. For students and researchers, Spiller’s contributions offer a compelling model of how to translate complex guidance and AI problems into tangible, mission-ready solutions.