Danilo Vettorazzi

Universidade Federal do Rio de Janeiro

Papers

1

Total Citations

5

H-Index

1

About

Danilo Vettorazzi’s research centers on autonomous robotics, with a particular focus on motion planning and path optimization in real-world environments. His major contribution lies in the critical evaluation of Probabilistic Roadmap (PRM) methods, a cornerstone technique for robot navigation. In his most cited work, Vettorazzi systematically analyzed the performance of various PRM algorithms through extensive simulations, providing a practical guide for selecting the most effective approach in actual, unstructured settings. This work, with 5 citations, offers essential insights for researchers and engineers seeking to deploy robots beyond controlled labs. By bridging the gap between theoretical path planning and real-world application, Vettorazzi’s analysis helps clarify which methods are best suited for specific environmental constraints. His research is valuable for students and practitioners in robotics, artificial intelligence, and autonomous systems, offering a data-driven foundation for improving robot autonomy and reliability in complex, dynamic spaces.

Research Focus

Key Achievements

1
H-Index
1
Papers
5
Total Citations
5
Avg Citations/Paper
🏆 Most Cited Paper
Wich Probabilistic Roadmap method should be used by a robot in an actual environment? An analysis of the main methods through simulations
5 citations · 2016
📈 Most Prolific Year: 2016 (1 Papers)
🤝 Key Collaborators: 3
🏛 Institutions: Universidade Federal do Rio de Janeiro

Top Papers

  1. 1

Key Collaborators

Contact & Links

Available for collaboration
Content generated · 12 days ago