Papers
6
Total Citations
80
H-Index
5
About
Andrea Fusiello is a leading researcher at the intersection of computer vision, robotics, and 3D mapping. His work spans from foundational computer vision theory to applied autonomous systems, with a particular focus on enabling machines to perceive and navigate complex environments. A major contribution is his pioneering application of Procrustes analysis for the virtual trial assembly of large-scale elements, a technique that has garnered 29 citations for its impact on industrial manufacturing. Fusiello’s early work on rate-monotonic scheduling for hard-real-time systems (19 citations) remains a cornerstone in embedded systems design. He has also made significant strides in autonomous indoor mapping, developing systems that combine LiDAR SLAM with deep learning-based people detection to create robust maps in crowded, dynamic spaces. His research on synthesizing indoor maps under uncertainty (11 citations) laid the groundwork for modern robotic exploration. With a career spanning from 3D vision for structure and motion estimation to comparative studies of handheld versus mobile mapping systems, Fusiello’s work is essential reading for anyone interested in how robots see, map, and move through the world.
Research Focus
Key Achievements
Top Papers
- 1Procrustes analysis for the virtual trial assembly of large-size elements29 citations · 2019
- 2Rate-monotonic scheduling for hard-real-time systems19 citations · 1997
- 3Synthesis of indoor maps in presence of uncertainty11 citations · 1997
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- 6THREE-DIMENSIONAL VISION FOR STRUCTURE AND MOTION ESTIMATION4 citations · 1999