Point Cloud Processing
Showing 7 of 7 projects
A standalone, large-scale open-source library for 2D/3D image and point cloud processing.
A computationally efficient and robust LiDAR-inertial odometry (LIO) package using a tightly-coupled iterated Kalman filter.
A curated list of papers, datasets, and code for 3D point cloud analysis research, covering classification, segmentation, detection, and more.
A lightweight, ground-optimized lidar odometry and mapping system for ROS-compatible unmanned ground vehicles.
A clean, simplified implementation of the LOAM algorithm for real-time LiDAR odometry and mapping using Eigen and Ceres Solver.
A ROS package for robot-centric elevation mapping that handles pose uncertainty for navigation on rough terrain.
A realtime LiDAR odometry and mapping (LOAM) method for state estimation and mapping using 3D lidar sensors like Velodyne VLP16.
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