Stefano Carlo Lambertenghi
Papers
1
Total Citations
13
H-Index
1
About
Stefano Carlo Lambertenghi is a leading researcher in swarm robotics and edge AI, specializing in ultra-low-power deep learning for autonomous nano-drones. His work tackles the critical challenge of enabling precise relative localization among sub-40g, sub-100mW platforms—a fundamental requirement for scalable drone swarms. His most-cited paper, "Ultra-low Power Deep Learning-based Monocular Relative Localization Onboard Nano-quadrotors" (2023, 13 citations), introduces a novel end-to-end system that leverages deep neural networks for peer-to-peer monocular localization, achieving real-time performance on resource-constrained hardware. This contribution bridges the gap between deep learning and extreme edge computing, demonstrating that complex vision-based tasks can be executed onboard nano-drones without cloud reliance. Lambertenghi’s work has significant implications for applications like search-and-rescue, environmental monitoring, and distributed sensing, where lightweight, autonomous swarms must operate in GPS-denied environments. By pushing the boundaries of what is computationally possible on milliwatt-scale processors, he is helping to define the next generation of intelligent, collaborative micro-robots.
Research Focus
Key Achievements
Top Papers
- 1