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20242026
most citedSAHA: Supervised Autonomous HArvester for selective forest thinning

2 citations · 4 across the 5 of their papers we have counts for

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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.RO2026★ 2 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.RO2025★ 1 cited

Efficiently Closing Loops in LiDAR-Based SLAM Using Point Cloud Density Maps

Saurabh Gupta, Tiziano Guadagnino, Benedikt Mersch +3

Consistent maps are key for most autonomous mobile robots, and they often use SLAM approaches to build such maps. Loop closures via place recognition help to maintain accurate pose…

cs.RO2024★ 1 cited

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…