Papers
6
Total Citations
64
H-Index
5
About
F. Giannone is a robotics researcher whose work bridges autonomous systems, artificial intelligence, and cultural heritage preservation. His key research areas include policy gradient learning for legged robots, edge computing with 5G, and robotic digitization of archaeological sites. Giannone’s most cited work, "Policy gradient learning for a humanoid soccer robot" (2009, 16 citations), demonstrates his foundational contributions to reinforcement learning in robotics, enabling robots to acquire complex locomotion and gameplay skills through trial-and-error optimization. He extended these ideas to quadruped robots (2010, 11 citations) and layered learning with 3D simulators (2008, 11 citations), advancing the RoboCup domain. A notable achievement is his 2020 paper on remote robot control combining 5G, AI, and GPU image processing at the edge (12 citations), which showcased a low-latency system for slalom navigation—a practical demonstration of real-time intelligent control. Giannone also pioneered robotic digitization for cultural heritage, introducing the DigiRo platform (2017, 9 citations) and a cloud-based approach to managing archaeological site models (2015, 5 citations). His work has accumulated over 64 citations, reflecting its interdisciplinary impact across robotics, AI, and heritage science.
Research Focus
Key Achievements
Top Papers
- 1Policy gradient learning for a humanoid soccer robot16 citations · 2009
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- 3Policy gradient learning for quadruped soccer robots11 citations · 2010
- 4Layered Learning for a Soccer Legged Robot Helped with a 3D Simulator11 citations · 2008
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