2 citations · 2 across the 8 of their papers we have counts for
9 papers
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…
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…
Learning Where to Look: Self-supervised Viewpoint Selection for Active Localization using Geometrical Information
Luca Di Giammarino, Boyang Sun, Giorgio Grisetti +3
Accurate localization in diverse environments is a fundamental challenge in computer vision and robotics. The task involves determining a sensor's precise position and orientation,…
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…
VBR: A Vision Benchmark in Rome
Leonardo Brizi, Emanuele Giacomini, Luca Di Giammarino +4
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 visua…
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…