Davide De Pazzi

Papers

Total Citations

H-Index

About

Davide De Pazzi is a researcher at the forefront of sensor fusion and robotic perception, with a primary focus on integrating LiDAR, thermal imaging, and SLAM (Simultaneous Localization and Mapping) technologies. His most cited work, "3D Radiometric Mapping by Means of LiDAR SLAM and Thermal Camera Data Fusion" (2022), introduces a pioneering system that fuses infrared thermal data with 3D LiDAR point clouds to produce large-scale radiometric maps. This innovation directly addresses critical needs in rover navigation, industrial plant monitoring, and rescue robotics, enabling machines to "see" temperature variations in complex environments. With 13 citations, this paper has already established De Pazzi as a key contributor to multi-modal mapping. His research bridges the gap between geometric and thermal data, offering practical solutions for autonomous systems operating in low-visibility or hazardous conditions. By advancing the accuracy and utility of 3D thermal mapping, De Pazzi is shaping the future of field robotics and environmental sensing, making his work essential reading for engineers and scientists developing next-generation perception systems.