LIO-SAM: Tightly-coupled Lidar Inertial Odometry via Smoothing and Mapping
A computationally efficient and robust LiDAR-inertial odometry (LIO) package
Track Advancement of SLAM 跟踪SLAM前沿动态【2021 version】業務調整，暫停更新
A Robust, Real-time, RGB-colored, LiDAR-Inertial-Visual tightly-coupled state Estimation and mapping package
LVI-SAM: Tightly-coupled Lidar-Visual-Inertial Odometry via Smoothing and Mapping
[IROS2022] Robust Real-time LiDAR-inertial Initialization Method.
[IEEE RA-L & ICRA'22] A lightweight and computationally-efficient frontend LiDAR odometry solution with consistent and accurate localization.
LeGO-LOAM, LIO-SAM, LVI-SAM, FAST-LIO2, Faster-LIO, VoxelMap, R3LIVE, Point-LIO, KISS-ICP, DLO, DLIO, Ada-LIO, PV-LIO, SLAMesh, ImMesh, FAST-LIO-MULTI, M-LOAM, LOCUS, SLICT, MA-LIO, CT-ICP, GenZ-ICP, ...
A simple localization framework that can re-localize in built maps based on FAST-LIO.
[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 probabilistic voxelmap-based LiDAR-Inertial Odometry.
ICRA 2021 - Robust Place Recognition using an Imaging Lidar
GenZ-ICP: SOTA robust LiDAR odometry (IEEE RA-L 2025)
Self-supervised Deep LiDAR Odometry for Robotic Applications
EU Long-term Dataset with Multiple Sensors for Autonomous Driving
[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
