2 citations · 2 across the 7 of their papers we have counts for
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Breaking Time: A Fully Gaussian Framework for Distributed and Continuous-Time SLAM
Davide Ceriola, Simone Ferrari, Luca Di Giammarino +2
Continuous-time SLAM provides a principled framework for fusing heterogeneous sensors while estimating smooth trajectories, and is particularly well-suited for handling heterogeneo…
DRO: Doppler-Aware Direct Radar Odometry
Cedric Le Gentil, Leonardo Brizi, Daniil Lisus +3
A renaissance in radar-based sensing for mobile robotic applications is underway. Compared to cameras or lidars, millimetre-wave radars have the ability to `see' through thin walls…
Splat-LOAM: Gaussian Splatting LiDAR Odometry and Mapping
Emanuele Giacomini, Luca Di Giammarino, Lorenzo De Rebotti +2
LiDARs provide accurate geometric measurements, making them valuable for ego-motion estimation and reconstruction tasks. Although its success, managing an accurate and lightweight…
MAD-BA: 3D LiDAR Bundle Adjustment -- from Uncertainty Modelling to Structure Optimization
Krzysztof Ćwian, Luca Di Giammarino, Simone Ferrari +3
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…
MAD-ICP: It Is All About Matching Data -- Robust and Informed LiDAR Odometry
Simone Ferrari, Luca Di Giammarino, Leonardo Brizi +1
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 m…
CaLib: Simple and Accurate LiDAR-RGB Calibration using Small Common Markers
Emanuele Giacomini, Leonardo Brizi, Luca Di Giammarino +3
In many fields of robotics, knowing the relative position and orientation between two sensors is a mandatory precondition to operate with multiple sensing modalities. In this conte…