Carmine Caponio
Papers
1
Total Citations
3
H-Index
1
About
Carmine Caponio is an emerging researcher specializing in mobile robotics, autonomous systems, and intelligent control, with a particular focus on automated driving technologies and path-following methodologies. His work bridges theoretical modeling and real-world experimental validation, a hallmark of rigorous engineering research. Caponio's most notable contribution to date is his 2024 study on scaled robotic vehicles, where he developed and validated a comprehensive framework integrating modeling, positioning, and deep reinforcement learning for path-following control. This work addresses a critical challenge in automated driving systems — generating precise steering commands — and demonstrates how scaled robotic platforms can serve as effective, cost-efficient test benches for evaluating autonomous driving functions across industrial environments such as warehousing and manufacturing. Having already attracted 3 citations shortly after publication, the work signals growing interest from the robotics and autonomous systems community. Caponio's research stands at the intersection of machine learning and robotics, leveraging deep reinforcement learning to push the boundaries of what scaled autonomous platforms can achieve. For students and researchers exploring intelligent vehicle control and indoor autonomous navigation, his experimental and algorithmically rigorous approach offers a valuable and forward-looking perspective.
Research Focus
Key Achievements
Top Papers
- 1