Gabriele Coffetti

Papers

Total Citations

H-Index

About

Gabriele Coffetti is a leading researcher at the intersection of human-robot interaction (HRI), collaborative robotics, and augmented reality (AR). His work focuses on making industrial robots more intuitive and accessible, moving beyond traditional programming methods toward natural, gesture-based control. Coffetti’s most influential contribution is **MEGURU**, a gesture-based robot program builder for meta-collaborative workstations (43 citations), which redefines how humans and robots can co-create tasks in shared spaces. He is also the creator of the **HANDS dataset** (28 citations), a meticulously curated RGB-D resource featuring 15 static hand gestures—including single and two-handed poses—designed to train robust vision systems for real-time HRI. In parallel, his **Hands-Free** teleoperation system (16 citations) leverages OpenPose neural networks to enable operators to control a robot end-effector via hand gestures in an AR environment, eliminating the need for physical controllers. Coffetti’s work is notable for its practical, data-driven approach: by combining custom datasets, neural architectures, and AR interfaces, he is paving the way for safer, more fluid human-robot collaboration in manufacturing and beyond. His research is essential reading for anyone interested in the future of intuitive robot programming and vision-based interaction.