Luca Lobefaro
Papers
5
Total Citations
39
H-Index
4
About
Luca Lobefaro is a robotics researcher whose work sits at the intersection of agricultural and forestry automation, specializing in how robots perceive and interact with dynamic, unstructured natural environments. His core research areas include LiDAR-based mapping, spatio-temporal data association, and 3D scene understanding for growing plants and forest ecosystems. Lobefaro’s major contributions lie in developing systems that enable robots to track and model changing geometry over time—critical for tasks like automated phenotyping and precision forestry. His most cited paper, “Estimating 4D Data Associations Towards Spatial-Temporal Mapping of Growing Plants for Agricultural Robots” (2023, 12 citations), tackles the fundamental challenge of associating 3D points across time as plants grow. He also led the creation of the “Digiforests” dataset (2025, 9 citations), a longitudinal LiDAR benchmark that is already shaping research in forestry robotics. Other notable works include “Kinematic-ICP” (2025, 8 citations), which enhances odometry for wheeled robots on planar surfaces, and methods for tree instance segmentation and trait estimation from mobile LiDAR (2024, 6 citations). With a growing citation record and a focus on real-world deployment, Lobefaro is helping to build the perceptual foundations for robots that can autonomously monitor and manage our living landscapes.
Research Focus
Key Achievements
Top Papers
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- 2Digiforests: a Longitudinal Lidar Dataset for Forestry Robotics9 citations · 2025
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