Giovanni Zanotti
Papers
1
Total Citations
2
H-Index
1
About
Giovanni Zanotti is a researcher at Politecnico di Milano’s ASTRA team, specializing in vision-based navigation and deep learning for autonomous spacecraft landing. His work focuses on developing AI-driven systems that enable pinpoint lunar landings, particularly in challenging environments like the Moon’s South Pole. Zanotti’s key contribution lies in the experimental validation of synthetic training sets for deep learning navigation, demonstrating that artificially generated imagery can effectively train neural networks to guide a spacecraft during descent—from 100 km altitude down to 3 km. This approach reduces reliance on real-world lunar data, which is scarce and costly to obtain. His most-cited paper (2020) has garnered 2 citations, reflecting early but growing interest in this niche. Notably, his research addresses a critical bottleneck in autonomous space exploration: reliable terrain-relative navigation under extreme lighting and surface conditions. By bridging computer vision and aerospace engineering, Zanotti’s work paves the way for safer, more precise landings on the Moon and beyond, with potential applications for future Artemis missions and planetary exploration.
Research Focus
Key Achievements
Top Papers
- 1