Papers
12
Total Citations
322
H-Index
7
About
Giancarlo Troni is a robotics researcher whose work spans underwater robotics, autonomous navigation, sensor calibration, and agricultural and field robotics. He is perhaps best known for his groundbreaking contributions to underwater robotic mapping, most notably his 2016 paper on vision-based 3D reconstruction for underwater archaeology, which has garnered 134 citations and demonstrated how autonomous underwater vehicles (AUVs) and diver-controlled stereo systems can document submerged archaeological sites at unprecedented resolution. His research has significantly advanced the state of underwater vehicle navigation through novel methods for adaptive estimation of sensor bias in magnetometers and accelerometers, and improved Doppler-based attitude estimation — work that addresses fundamental accuracy limitations in real-world robotic deployments. Beyond underwater systems, Troni has expanded into precision agriculture, contributing a widely cited pattern recognition strategy for visual grape bunch detection in vineyards (92 citations), and into deep learning-based sonar odometry for AUVs. His interdisciplinary reach also includes educational initiatives in robotics for developing countries and hydraulic manipulator control for mining applications. With over 300 cumulative citations, Troni's career reflects a consistent commitment to bridging theoretical rigor with practical, field-tested robotic solutions.
Research Focus
Key Achievements
Top Papers
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- 2A pattern recognition strategy for visual grape bunch detection in vineyards92 citations · 2018
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