Papers
25
Total Citations
188
H-Index
8
About
Renan Maffei is a roboticist whose research lies at the intersection of autonomous navigation, semantic perception, and field robotics. His work addresses core challenges in enabling mobile robots to operate safely and intelligently in complex, unstructured environments—both indoors and outdoors. Maffei’s most influential contribution is a novel approach to traversability analysis using semantic terrain segmentation (24 citations), which allows robots to understand and navigate outdoor terrains by classifying ground surfaces, a critical capability for search-and-rescue, patrolling, and delivery missions. He has also made significant advances in integrated exploration, notably through the Ouroboros system (15 citations), which uses potential fields to close loops in unexplored regions, and through time-based potential rails for efficient map-building. In localization, Maffei has pioneered hybrid methods combining Monte Carlo and set-membership techniques for underwater robots (12 citations), as well as vision-based global localization using ceiling space density (8 citations). His work on autonomous UV-C disinfection (10 citations) directly addressed COVID-19 challenges, demonstrating real-world impact. With over 120 total citations, Maffei’s research continues to push the boundaries of autonomous robot perception and navigation.
Research Focus
Key Achievements
Top Papers
- 1Traversability Analysis by Semantic Terrain Segmentation for Mobile Robots24 citations · 2021
- 2
- 3Ouroboros: Using potential field in unexplored regions to close loops15 citations · 2015
- 4
- 5
- 6Integrated exploration using time-based potential rails11 citations · 2014
- 7Autonomous Environment Disinfection Based on Dynamic UV-C Irradiation Map10 citations · 2022
- 8Fast Monte Carlo Localization using spatial density information9 citations · 2015
- 9
- 10Vision-Based Global Localization Using Ceiling Space Density8 citations · 2018