Gino Innero

Papers

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About

Gino Innero is a leading researcher in industrial automation and robotics, with a focus on transforming warehouse logistics through intelligent mobile manipulation. His work centers on developing autonomous systems for palletizing and depalletizing tasks, integrating advanced 3D perception, machine vision, and collaborative robotics to enhance flexibility and safety in dynamic environments. Innero's most-cited paper, "Toward Future Automatic Warehouses: An Autonomous Depalletizing System Based on Mobile Manipulation and 3D Perception" (2021, 28 citations), introduces a mobile platform that combines mechanical design and control to automate item extraction from pallets, significantly improving deployment ease. His earlier work, "Development of a Mobile Robotized System for Palletizing Applications" (2020, 17 citations), addresses the challenge of assembling heterogeneous pallets while ensuring safe human-robot interaction. These contributions have earned him recognition for advancing the state of the art in logistics automation, with his systems paving the way for more adaptive and efficient warehouses. Innero's research is highly cited for its practical impact, bridging the gap between theoretical robotics and real-world industrial applications.