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Simone Ferrari

4 accepted papers

2026

MAD-BA: 3D LiDAR Bundle Adjustment -- from Uncertainty Modelling to Structure Optimization

Krzysztof Cwian, Luca Di Giammarino, Simone Ferrari, Thomas Alessandro Ciarfuglia, Giorgio Grisetti, Piotr Skrzypczynski
ICRA 2026poster

The joint optimization of sensor poses and 3D structure is fundamental for state estimation in robotics and related fields. Current LiDAR systems often prioritize pose optimization, with structure refinement either omitted or treated separately using implicit representations. This paper introduces a…

Cited by 0Source ↗PDF ↗Scholar ↗
2025

MAD-BA: 3D LiDAR Bundle Adjustment - From Uncertainty Modelling to Structure Optimization

Krzysztof Cwian, Luca Di Giammarino, Simone Ferrari, Thomas A. Ciarfuglia, Giorgio Grisetti, Piotr Skrzypczynski
RA-L 2025

The joint optimization of sensor poses and 3D structure is fundamental for state estimation in robotics and related fields. Current LiDAR systems often prioritize pose optimization, with structure refinement either omitted or treated separately using implicit representations. This paper introduces a

Cited by 3Source ↗Scholar ↗
2024

MAD-ICP: It is All About Matching Data - Robust and Informed LiDAR Odometry

Simone Ferrari, Luca Di Giammarino, Leonardo Brizi, Giorgio Grisetti
RA-L 2024

LiDAR odometry is the task of estimating the ego-motion of the sensor from sequential laser scans. This problem has been addressed by the community for more than two decades, and many effective solutions are available nowadays. Most of these systems implicitly rely on assumptions about the operating

Cited by 25Source ↗code ↗Scholar ↗
2024

VBR: A Vision Benchmark in Rome

Leonardo Brizi, Emanuele Giacomini, Luca Di Giammarino, Simone Ferrari, Omar Salem, Lorenzo De Rebotti +1
ICRA 2024poster

This paper presents a vision and perception research dataset collected in Rome, featuring RGB data, 3D point clouds, IMU, and GPS data. We introduce a new benchmark targeting visual odometry and SLAM, to advance the research in autonomous robotics and computer vision. This work complements existing…

Cited by 8Source ↗code ↗Scholar ↗