Roberto Aparici Marino

University of Genoa, University of Messina

Papers

Total Citations

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About

Roberto Aparici Marino is a robotics researcher whose work bridges the gap between autonomous navigation and emerging distributed intelligence. His primary research areas include quadrotor navigation, multi-floor indoor mapping, and the integration of federated learning into robotic networks. Aparici Marino’s most cited work, “A Minimalistic Quadrotor Navigation Strategy for Indoor Multi-floor Scenarios” (2015, 12 citations), introduces a lightweight, computationally efficient approach for drones to navigate complex indoor environments—a foundational contribution to autonomous aerial robotics. More recently, he has ventured into cutting-edge territory with “When Robotics Meets Distributed Learning: the Federated Learning Robotic Network Framework” (2023, 2 citations), which proposes a novel architecture for collaborative, privacy-preserving machine learning across robotic systems. This work leverages federated learning’s ability to solve large-scale problems using local data exclusively, positioning Aparici Marino at the forefront of decentralized robotics. His research holds promise for applications ranging from healthcare data analysis to real-time object recognition in video streams, showcasing his ability to adapt advanced computational paradigms to physical systems. Though early in his career, his work signals a thoughtful shift toward scalable, secure, and cooperative robotic networks.