A collection of GTSAM factors and optimizers for point cloud SLAM
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Updated
Sep 12, 2024 - C++
A collection of GTSAM factors and optimizers for point cloud SLAM
Probably the fastest C++ dbscan library.
A C++ header only library for fast nearest neighbor and range searches using a KdTree. It supports interfacing with Eigen, OpenCV, and custom data types and provides optional Python bindings.
generic DBSCAN on CPU & GPU
Implementations of different algorithms for building Euclidean minimum spanning tree in k-dimensional space.
a super lightweight head-only 3d kdtree library based on nanoflann
Collision detection for 3D shapes. Axis-aligned bounding boxes (AABB).
Sensor Fusion Nanodegree (Udacity) Projects.
LiDAR processing ROS2. Segmentation: "Fast Ground Segmentation for 3D LiDAR Point Cloud Based on Jump-Convolution-Process". Clustering: "Curved-Voxel Clustering for Accurate Segmentation of 3D LiDAR Point Clouds with Real-Time Performance".
Point Cloud processing (VoxelGrid Downsampling, RANSAC Segmentation, KDTree Euclidean Clustering) for obstacle detection for autonomous vehicles.
Library for a collection of commnly used data structures
Use a KD-tree to perform the nearest neighbor search on a point cloud.
Database Management Systems course projects
Point-based Individual Tree Delineation from 3D LiDAR Point Cloud Data.
An optimized, single-header kD-Tree library for points written in C++11.
Header-only C++ K-d tree library
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