Lorenzo Sorgi

Philadelphia University, Italian Aerospace Research Centre, California University of Pennsylvania

Papers

Total Citations

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About

Lorenzo Sorgi is a researcher whose work lies at the intersection of computer vision and robotic navigation, with a particular focus on omnidirectional imaging. His primary contributions involve developing algorithms to process spherical images—those captured by panoramic sensors—for robust attitude estimation and localization. In his most-cited work, "Rotation estimation from spherical images" (2004, 34 citations), Sorgi addressed a critical challenge in robotics: using the panoramic field of view to solve localization tasks without relying on traditional landmarks. He further advanced this field with "Normalized Cross-Correlation for Spherical Images" (2004, 17 citations) and "Template gradient matching in spherical images" (2004, 8 citations), where he proposed methods for matching visual templates across spherical views, enabling global navigation and formation control. These techniques leverage the persistence of appearance in omnidirectional images, allowing robots to navigate more reliably in unstructured environments. Sorgi’s work has been foundational for researchers developing vision-based autonomous systems, and his papers remain cited for their practical, geometry-driven solutions to real-world robotic challenges.