Nicolas Pieper Bortoluzzi
Papers
2
Total Citations
18
H-Index
2
About
Nicolas Pieper Bortoluzzi is a robotics researcher specializing in autonomous navigation and reinforcement learning for aerial and hybrid vehicles. His work focuses on developing intelligent systems capable of operating in challenging, unstructured environments without external intervention. Bortoluzzi’s most-cited paper, “Visual-based Autonomous Unmanned Aerial Vehicle for Inspection in Indoor Environments” (2020, 16 citations), introduces a fully self-contained UAV that performs navigation tasks using only onboard visual processing, eliminating the need for off-board computation or human operators—a significant step toward practical, autonomous inspection robots. He has also explored cutting-edge Deep Reinforcement Learning techniques, as in his 2021 paper on mapless navigation for a Hybrid Aerial Underwater Vehicle (HAUV) during medium transition. This work applies Deep Q-Learning to continuous action domains, enabling a single vehicle to seamlessly move between air and water. Though early in his career, Bortoluzzi’s contributions demonstrate a clear trajectory toward robust, adaptive autonomy for inspection and exploration robots. His research bridges perception, control, and learning, offering promising solutions for real-world deployment in confined or hazardous settings.
Research Focus
Key Achievements
Top Papers
- 1
- 2