LIO-SAM: Tightly-coupled Lidar Inertial Odometry via Smoothing and Mapping
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Updated
Jul 11, 2024 - C++
LIO-SAM: Tightly-coupled Lidar Inertial Odometry via Smoothing and Mapping
A computationally efficient and robust LiDAR-inertial odometry (LIO) package
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
[IEEE RA-L & ICRA'22] A lightweight and computationally-efficient frontend LiDAR odometry solution with consistent and accurate localization.
[IROS2022] Robust Real-time LiDAR-inertial Initialization Method.
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.
ICRA 2021 - Robust Place Recognition using an Imaging Lidar
A probabilistic voxelmap-based LiDAR-Inertial Odometry.
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
Easy description to run and evaluate Lego-LOAM with KITTI-data
Easy description to run and evaluate A-LOAM with KITTI-data
[IROS 2023] Fast LiDAR-Inertial Odometry via Incremental Plane Pre-Fitting and Skeleton Tracking
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