Papers
6
Total Citations
53
H-Index
3
About
Edoardo Topini is a robotics researcher advancing the autonomy of underwater vehicles, with a focus on intelligent perception, planning, and adaptive control. His work addresses critical challenges in Autonomous Underwater Vehicles (AUVs) for inspection, intervention, and survey tasks in unknown environments. Topini’s most cited paper, “Deep Learning for on-board AUV Automatic Target Recognition for Optical and Acoustic imagery” (2020, 29 citations), pioneers real-time, onboard classification of underwater targets, enabling vehicles to understand and engage their surroundings without human intervention. He further extends AUV autonomy through “Multi-Hypothesis Task Planning” (2023, 10 citations), integrating temporal AI planning with semantic world modeling to guarantee data quality during inspections. His research on reconfigurable vehicles, including dynamic maneuverability analysis and navigation control systems, supports versatile platforms capable of free-floating intervention and survey tasks. Topini also contributed to the SUONO project, advancing underwater manipulation systems, and led the UNIFI Robotics Team’s participation in the RAMI 2023 competition with the FeelHippo AUV. With a growing citation record and a focus on closing the loop between perception, planning, and action, Topini is shaping the next generation of truly autonomous underwater robots for scientific and industrial missions.
Research Focus
Key Achievements
Top Papers
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- 5RAMI 2023: The Experience of the UNIFI Robotics Team with FeelHippo AUV2 citations · 2024
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