Matteo Finotto

Papers

Total Citations

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About

Matteo Finotto is a researcher whose work sits at the intersection of robotics, computer vision, and intelligent manufacturing. His key contributions include developing innovative methods for humanoid robot stabilization using omnidirectional vision, a technique that leverages wide-field cameras to estimate pitch, roll, and yaw in real time—enabling more robust bipedal locomotion. His most-cited paper, "Humanoid Gait Stabilization based on Omnidirectional Visual Gyroscope" (2009, 5 citations), adapts existing attitude estimation methods for practical, real-time applications, demonstrating how visual cues can replace or augment traditional inertial sensors. Finotto also contributed to manufacturing automation through the "WorkCellSimulator" (2012, 5 citations), a 3D simulation tool for intelligent production environments, and a constraint-based motion optimization system for quality inspection (2014, 2 citations). While his citation counts are modest, his work reflects a hands-on, interdisciplinary approach—bridging theoretical vision algorithms with tangible robotic and industrial systems. Finotto’s research is particularly valuable for students and engineers interested in low-cost sensor fusion, real-time control, and simulation-driven manufacturing.