activity
20242026
most citedSAHA: Supervised Autonomous HArvester for selective forest thinning

2 citations · 2 across the 2 of their papers we have counts for

collaborators

5 papers

cs.RO2026

DigiForest: Digital Analytics and Robotics for Sustainable Forestry

Marco Camurri, Enrico Tomelleri, Matías Mattamala +18

Covering one third of Earth's land surface, forests are vital to global biodiversity, climate regulation, and human well-being. In Europe, forests and woodlands reach approximately…

cs.RO20262 cited

SAHA: Supervised Autonomous HArvester for selective forest thinning

Fang Nan, Meher Malladi, Qingqing Li +7

Forestry plays a vital role in our society, creating significant ecological, economic, and recreational value. Efficient forest management involves labor-intensive and complex oper…

cs.RO2025

A Robust Approach for LiDAR-Inertial Odometry Without Sensor-Specific Modeling

Meher V. R. Malladi, Tiziano Guadagnino, Luca Lobefaro +1

Accurate odometry is a critical component in a robotic navigation stack, and subsequent modules such as planning and control often rely on an estimate of the robot's motion. Sensor…

cs.CV2025

3D Hierarchical Panoptic Segmentation in Real Orchard Environments Across Different Sensors

Matteo Sodano, Federico Magistri, Elias Marks +6

Crop yield estimation is a relevant problem in agriculture, because an accurate yield estimate can support farmers' decisions on harvesting or precision intervention. Robots can he…

cs.RO2024

Kinematic-ICP: Enhancing LiDAR Odometry with Kinematic Constraints for Wheeled Mobile Robots Moving on Planar Surfaces

Tiziano Guadagnino, Benedikt Mersch, Ignacio Vizzo +5

LiDAR odometry is essential for many robotics applications, including 3D mapping, navigation, and simultaneous localization and mapping. LiDAR odometry systems are usually based on…