LIO-SAM: Tightly-coupled Lidar Inertial Odometry via Smoothing and Mapping
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Updated
Sep 10, 2024 - C++
LIO-SAM: Tightly-coupled Lidar Inertial Odometry via Smoothing and Mapping
A Robust, Real-time, RGB-colored, LiDAR-Inertial-Visual tightly-coupled state Estimation and mapping package
A LiDAR odometry pipeline that just works
[IEEE RA-L & ICRA'22] A lightweight and computationally-efficient frontend LiDAR odometry solution with consistent and accurate localization.
ImMesh: An Immediate LiDAR Localization and Meshing Framework
[IEEE ICRA'23] A new lightweight LiDAR-inertial odometry algorithm with a novel coarse-to-fine approach in constructing continuous-time trajectories for precise motion correction.
A 3D point cloud descriptor for place recognition
LiDAR SLAM = FAST-LIO + Scan Context
Robust LiDAR SLAM with a versatile plug-and-play loop closing and pose-graph optimization.
Tightly-coupled Direct LiDAR-Inertial Odometry and Mapping Based on Cartographer3D.
A real-time, direct and tightly-coupled LiDAR-Inertial SLAM for high velocities with spinning LiDARs
A SLAM implementation combining FAST-LIO2 with pose graph optimization and loop closing based on Quatro and Nano-GICP
[IROS 2023] Fast LiDAR-Inertial Odometry via Incremental Plane Pre-Fitting and Skeleton Tracking
a SLAM implementation combining FAST-LIO2 with pose graph optimization and loop closing based on LIO-SAM paper
MD-SLAM: Multi-cue Direct SLAM. Implements the first photometric LiDAR SLAM pipeline, that works withouth any explicit geometrical assumption. Universal approach, working independently for RGB-D and LiDAR.
A Map-based localization implementation combining FAST-LIO2 as an odometry with Quatro + Nano-GICP as a map matching method
🔥 💪 Official Project: A Robust and Effective LiDAR-SLAM System with Learning-based Denoising and Loop Closure (DLC-SLAM, TMECH-2023)
Real-Time Simultaneous Localization and Mapping with LiDAR intensity
A CUDA reimplementation of the line/plane odometry of LIO-SAM. A point cloud hash map (inspired by iVox of Faster-LIO) on GPU is used to accelerate 5-neighbour KNN search.
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