LiLi-OM is a tightly-coupled, keyframe-based LiDAR-inertial odometry and mapping system for both solid-state-LiDAR and conventional LiDARs.

3D LIDAR-based Graph SLAM

LeGO-LOAM: Lightweight and Ground-Optimized Lidar Odometry and Mapping on Variable Terrain

A simple localization framework that can re-localize in built maps based on FAST-LIO.

A Lidar-Inertial State Estimator for Robust and Efficient Navigation based on iterated error-state Kalman filter

LIO-SAM: Tightly-coupled Lidar Inertial Odometry via Smoothing and Mapping

LiDAR SLAM = FAST-LIO + Scan Context

LiDAR-Inertial 3D Plane Simulator

A computationally efficient and robust LiDAR-inertial odometry (LIO) package

Laser Odometry and Mapping (Loam) is a realtime method for state estimation and mapping using a 3D lidar.

[IEEE RA-L & ICRA'22] A lightweight and computationally-efficient frontend LiDAR odometry solution with consistent and accurate localization.

A collection of GICP-based fast point cloud registration algorithms

Faster-LIO: Lightweight Tightly Coupled Lidar-inertial Odometry using Parallel Sparse Incremental Voxels

CT-ICP: Continuous-Time LiDAR Odometry

[RA-L 2022] An efficient and probabilistic adaptive voxel mapping method for LiDAR odometry

A LiDAR-Inertial Odometry with Efficient Local Geometric Information Estimation

A LiDAR-Inertial Odometry with Efficient Uncertainty Analysis.

🪙 COIN-LIO: Complementary Intensity-Augmented LiDAR Inertial Odometry (ICRA 2024)