Luca Bonamini

Papers

Total Citations

H-Index

About

Luca Bonamini is a researcher whose work sits at the intersection of robotics, autonomous systems, and perception, with a particular focus on enabling vehicles to navigate safely in extreme, GPS-denied environments. His most cited paper, "LiDAR-Based GNSS Denied Localization for Autonomous Racing Cars" (2020, 30 citations), addresses a critical challenge in autonomous driving: maintaining precise localization when satellite signals are unavailable. By leveraging LiDAR data, Bonamini’s work demonstrates how racing platforms can achieve high-speed, reliable state estimation—pushing the boundaries of what is possible in autonomous navigation under dynamic, high-risk conditions. This research not only advances the technical frontier for self-driving cars but also contributes foundational methods applicable to broader robotics and field robotics scenarios. Bonamini’s contributions are particularly notable for their practical impact in autonomous racing, a domain that serves as a rigorous testbed for algorithms that must perform under extreme latency and accuracy constraints. His work underscores the potential of LiDAR-based systems to bridge the gap between controlled testing and real-world deployment, making him a key figure in the ongoing evolution of robust, perception-driven autonomy.