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About

Roberto Pagani’s research sits at the intersection of robotics, human-robot interaction, and intelligent manufacturing, with a focus on making collaborative robots (cobots) more intuitive, precise, and safe for human partners. His major contributions span three key areas: dynamic modeling of industrial robots, vision-based human-robot interfaces, and practical calibration methods. In his highly cited work on friction identification (51 citations), Pagani demonstrated that joint friction in industrial manipulators follows a double exponential law during operation—a finding critical for improving robot control and predictive maintenance. He also created the HANDS dataset (28 citations), a rich RGB-D resource of static hand gestures designed to train gesture recognition systems for seamless human-robot collaboration. Pagani’s innovative “MEGURU” system (43 citations) enables gesture-based robot programming for meta-collaborative workstations, while his “Hands-Free” teleoperation method (16 citations) uses augmented reality and neural networks to allow operators to control robots with natural hand movements. His work on cobot user frame calibration (21 citations) and thermal-aware friction modeling (22 citations) further demonstrates his commitment to bridging theoretical modeling with real-world industrial applications. Pagani’s research has been widely adopted in both academic and industrial settings, with over 200 total citations, establishing him as a leading voice in the next generation of human-centered robotics.