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About

Andrea Bonci is a prominent researcher specializing in industrial robotics, human-robot interaction, autonomous systems, and smart manufacturing. His work sits at the intersection of Industry 4.0 and advanced automation, where he has made substantial contributions to how robots perceive, collaborate with, and adapt alongside human workers in modern industrial environments. Bonci's most influential contribution, a comprehensive survey on human-robot perception in industrial settings (2021, 152 citations), has become an essential reference for researchers navigating the complex landscape of collaborative robotics. His subsequent survey on Robot Operating System 2 (ROS2) frameworks (2023, 55 citations) further demonstrates his commitment to advancing robot autonomy and flexibility in manufacturing contexts. Beyond perception and middleware, Bonci has pioneered practical solutions in predictive maintenance, developing motor current signal analysis techniques that help factories proactively detect faults before costly failures occur. His broader research portfolio reflects a coherent vision of the "factory of the future," encompassing holonic cyber-physical systems, anomaly detection with concept drift adaptation, production efficiency metrics, and scalable cloud robotics architectures. More recently, his work on automating skilled manual tasks — such as composite material layup — illustrates his drive to push collaborative robots into increasingly demanding real-world applications. Across his career, Bonci's research has accumulated over 350 citations, marking him as a significant voice in intelligent industrial automation.