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The Point Cloud Library is a collection of C++ algorithms designed for filtering, registering, and analyzing large-scale 3D spatial datasets. It provides a framework for 3D point cloud processing, incorporating tools for spatial data filtering and geometric feature estimation. The library includes specialized systems for aligning multiple spatial datasets into a single unified coordinate system and a rendering engine for the visual inspection and analysis of processed point cloud data. It also features tools for calculating spatial descriptors to identify structural patterns and shapes within
CGAL is a software library that provides a comprehensive collection of computational geometry algorithms and data structures. It is built around a geometry kernel that defines fundamental geometric primitives and operations, enabling the construction of complex geometric objects and the computation of geometric predicates with exact arithmetic for reliable results. The library covers a wide range of geometric computation capabilities, including the construction of convex hulls, triangulations of point sets, and the generation of Voronoi diagrams. It also supports the processing of polygonal m
FAST_LIO is a real-time SLAM system and LiDAR-inertial odometry package designed for simultaneous localization and mapping. It functions as a state estimation engine and 3D mapping tool that fuses LiDAR point clouds with inertial measurement unit data to provide robust robot state estimation. The system utilizes a tightly-coupled sensor fusion approach with an iterative Kalman filter to estimate position and orientation. It distinguishes itself through direct point-to-plane matching, which calculates odometry by matching raw lidar points to the map surface without manual geometric feature ext
FAST-LIVO2 is a LiDAR-inertial odometry framework and factor-graph SLAM implementation designed for real-time robot localization and 3D mapping. It functions as a multi-sensor fusion pipeline and state estimator that integrates LiDAR, inertial, and camera inputs to track a robot's position and orientation. The system employs a tightly-coupled sensor fusion approach to maintain stable navigation, particularly in degraded environments. It utilizes a voxel-based 3D mapping tool to organize point clouds into volumetric grids, which optimizes memory usage and search speed during spatial reconstruc
An Efficient Probabilistic 3D Mapping Framework Based on Octrees. Contains the main OctoMap library, the viewer octovis, and dynamicEDT3D.
The main features of octomap/octomap are: Point Cloud Processing, Spatial Mapping.
Projects with overlapping indexed features include: pointcloudlibrary/pcl — The Point Cloud Library is a collection of C++ algorithms designed for filtering, registering, and analyzing… cgal/cgal — CGAL is a software library that provides a comprehensive collection of computational geometry algorithms and data… hku-mars/fast_lio — FAST_LIO is a real-time SLAM system and LiDAR-inertial odometry package designed for simultaneous localization and… open-mmlab/mmcv — mmcv is a foundation library for computer vision based on PyTorch. It provides a comprehensive system for constructing… hku-mars/fast-livo2 — FAST-LIVO2 is a LiDAR-inertial odometry framework and factor-graph SLAM implementation designed for real-time robot… microsoft/windows-universal-samples — This repository is a comprehensive collection of reference implementations and sample libraries for the Universal…