Papers
6
Total Citations
64
H-Index
4
About
Matteo Franchi is a robotics researcher whose work centers on underwater autonomous systems, navigation, and multi-robot collaboration in challenging marine environments. His most significant contribution lies in advancing localization and navigation strategies for Autonomous Underwater Vehicles (AUVs), where GPS signals are unavailable and reliable positioning remains a fundamental challenge. His 2020 paper on adaptive unscented Kalman filter-based navigation using 2D forward-looking SONAR has garnered 37 citations, establishing him as a notable voice in underwater state estimation. Franchi has extended this expertise into federated filtering architectures, developing acoustic-visual-inertial fusion approaches that enhance robustness for modern marine robots. Beyond single-vehicle systems, he has contributed to multi-robot frameworks through the DAMPS project, which tackles passive acoustic source localization using collaborative robot teams. His work also bridges practical robotics and environmental science, exploring how marine robots can support morphological monitoring of coastal ecosystems. Franchi's participation in international initiatives such as EUMarineRobots and competitive platforms like the European Robotics League further demonstrates the real-world applicability of his research, reflecting a career dedicated to pushing the boundaries of autonomous underwater exploration and perception.
Research Focus
Key Achievements
Top Papers
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