Jacopo Serafin
Papers
6
Total Citations
108
H-Index
5
About
Jacopo Serafin’s research lies at the intersection of robotics, computer vision, and autonomous navigation, with a particular focus on point cloud registration, traversability analysis, and field robotics. His most impactful work, “Using extended measurements and scene merging for efficient and robust point cloud registration” (2017, 38 citations), addresses a fundamental challenge in 3D mapping by improving the convergence and robustness of ICP algorithms through augmented measurement techniques. Earlier, his 2013 paper on “Efficient traversability analysis for mobile robots using the Kinect sensor” (32 citations) provided a practical, online solution for classifying terrain in real-time using low-cost sensors—a critical capability for autonomous navigation in unstructured environments. Serafin also contributed to cultural heritage robotics through the ROVINA project, where he explored mapping and digital preservation of catacombs and archaeological sites, demonstrating how mobile robots can operate in challenging, rescue-like scenarios. His work on “FLAT2D” (2016) advanced localization for autonomous vehicles by leveraging ground-surface intensity maps. With a total of over 100 citations across his publications, Serafin’s contributions have helped bridge the gap between robust perception algorithms and real-world robotic deployment, making him a notable figure in the field of mobile robotics and 3D mapping.
Research Focus
Key Achievements
Top Papers
- 1
- 2Efficient traversability analysis for mobile robots using the Kinect sensor32 citations · 2013
- 3Using Augmented Measurements to Improve the Convergence of ICP17 citations · 2014
- 4Exploration and mapping of catacombs with mobile robots12 citations · 2013
- 5FLAT2D: Fast localization from approximate transformation into 2D6 citations · 2016
- 6