Eleonora Maset
Papers
10
Total Citations
233
H-Index
7
About
Eleonora Maset is a leading researcher at the intersection of mobile robotics, 3D mapping, and precision agriculture. Her work centers on developing autonomous systems that can intelligently perceive and navigate complex, unstructured environments—from agricultural fields and forests to crowded indoor spaces. Maset’s major contributions include comprehensive surveys of supportive technologies for ground robotics in agriculture and rigorous, comparative evaluations of LiDAR and IMU-based SLAM algorithms for 3D robotic mapping. Her 2023 review on autonomous mapping in agriculture has already garnered 91 citations, underscoring its impact as a foundational resource for the field. She has also pioneered methods for repeatability assessment in robotic mapping and introduced deep learning-based people detection to enable safe autonomous navigation in dynamic, crowded settings. Beyond agriculture, Maset has explored the feasibility of SLAM-based point clouds for as-built modeling in architecture and construction. Her work on Procrustes analysis for virtual trial assembly of large-scale elements further demonstrates her versatility in solving real-world geometric challenges. Through her systematic benchmarking and field evaluations, Maset is helping to bridge the gap between robotic perception research and practical, deployable solutions for environmental monitoring and structural assessment.
Research Focus
Key Achievements
Top Papers
- 1
- 2Comparing LiDAR and IMU-based SLAM approaches for 3D robotic mapping47 citations · 2023
- 3
- 4Procrustes analysis for the virtual trial assembly of large-size elements29 citations · 2019
- 5Recent Trends in Mobile Robotics for 3D Mapping in Agriculture10 citations · 2022
- 6
- 7
- 8
- 9
- 10