Antonio Marino

Centre National de la Recherche Scientifique, University of Genoa

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About

Antonio Marino is a researcher at the forefront of robotics and autonomous systems, with key contributions spanning multi-agent coordination, human-robot interaction, and the theoretical foundations of graph neural networks. His work on input-state stability (ISS) of Gated Graph Neural Networks (2024, 7 citations) provides critical mathematical conditions for ensuring reliable, bounded behavior in learning-based control systems—a foundational step for deploying neural networks in safety-critical applications. In multi-UAV systems, Marino developed an end-to-end distributed trajectory generation algorithm (2024, 6 citations) that enables fleets of drones to navigate cluttered, dynamic environments using point cloud data, tackling the real-world challenge of collision avoidance without centralized planning. His comparative study of gestural and touchscreen interfaces for human-robot collaboration (2023, 5 citations) offers practical insights into designing intuitive, efficient interaction modalities that bridge the gap between human intent and robotic action. With a growing citation footprint and a focus on both theoretical rigor and applied robotics, Marino’s work is shaping how autonomous systems achieve stability, coordination, and seamless human integration.