Cataldo Guaragnella
Papers
7
Total Citations
119
H-Index
5
About
Cataldo Guaragnella is a researcher whose work spans human-robot interaction, autonomous robot navigation, and precision agriculture, with a growing body of contributions at the intersection of artificial intelligence, sensor technology, and robotics. He first gained significant recognition with his 2014 and 2015 work on gesture recognition systems using Microsoft Kinect sensors, combining neural networks and quaternion-based skeletal tracking to enable natural, intuitive communication between humans and service robots — a contribution that has attracted nearly 60 citations and remains influential in the HRI community. His research then expanded into robust autonomous navigation, contributing to the development of LOCUS, a high-precision multi-sensor LiDAR odometry system designed for real-time 3D mapping in demanding environments, which has garnered over 27 citations since its 2021 publication. Guaragnella has also applied his expertise to underwater robotics, proposing novel sonar video coding techniques for submersible platforms operating in low-visibility conditions. Most recently, his work has embraced precision viticulture, leveraging semantic segmentation and point cloud analysis to monitor vineyard biomass and improve crop sustainability. Together, these contributions reflect a researcher committed to advancing intelligent, sensor-driven systems across diverse and challenging real-world applications.
Research Focus
Key Achievements
Top Papers
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- 3A Neural Network Approach for Human Gesture Recognition with a Kinect Sensor13 citations · 2014
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