2 citations · 2 across the 10 of their papers we have counts for
11 papers
Unsigned Distance Maps on 2D Point Cloud Registration
Ricardo B. Sousa, Giorgio Grisetti, Héber Miguel Sobreira +2
2D point cloud registration arises in laser odometry and Simultaneous Localization and Mapping (SLAM) for mobile robots. Iterative Closest Point (ICP) is one of the most widely use…
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…
Resolution Where It Counts: Hash-based GPU-Accelerated 3D Reconstruction via Variance-Adaptive Voxel Grids
Lorenzo De Rebotti, Emanuele Giacomini, Giorgio Grisetti +1
Efficient and scalable 3D surface reconstruction from range data remains a core challenge in computer graphics and vision, particularly in real-time and resource-constrained scenar…
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…
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…
Enhancing LiDAR performance: Robust De-skewing Exclusively Relying on Range Measurements
Omar Salem, Emanuele Giacomini, Leonardo Brizi +2
Most commercially available Light Detection and Ranging (LiDAR)s measure the distances along a 2D section of the environment by sequentially sampling the free range along direction…