lidar-odometry
There are 22 repositories under lidar-odometry topic.
TixiaoShan / LIO-SAM
LIO-SAM: Tightly-coupled Lidar Inertial Odometry via Smoothing and Mapping
Language:C++ 3058YiChenCityU / Recent_SLAM_Research
Track Advancement of SLAM 跟踪SLAM前沿动态【2021 version】業務調整，暫停更新
RobustFieldAutonomyLab / LeGO-LOAM
LeGO-LOAM: Lightweight and Ground-Optimized Lidar Odometry and Mapping on Variable Terrain
Language:C++ 2266- Language:C++ 2229
hku-mars / r3live
A Robust, Real-time, RGB-colored, LiDAR-Inertial-Visual tightly-coupled state Estimation and mapping package
Language:C++ 1847LVI-SAM: Tightly-coupled Lidar-Visual-Inertial Odometry via Smoothing and Mapping
Language:C++ 1402- direct_lidar_odometry
vectr-ucla / direct_lidar_odometry
[IEEE RA-L & ICRA'22] A lightweight and computationally-efficient frontend LiDAR odometry solution with consistent and accurate localization.
Language:C++ 778 [IROS2022] Robust Real-time LiDAR-inertial Initialization Method.
Language:C++ 744engcang / SLAM-application
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 application and comparison on Gazebo and real-world datasets. Installation and config files are provided.
Language:Python 589HViktorTsoi / FAST_LIO_LOCALIZATION
A simple localization framework that can re-localize in built maps based on FAST-LIO.
Language:C++ 509[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.
Language:C++ 464ICRA 2021 - Robust Place Recognition using an Imaging Lidar
Language:C++ 393- Language:C++ 330
A probabilistic voxelmap-based LiDAR-Inertial Odometry.
Language:C++ 311leggedrobotics / delora
Self-supervised Deep LiDAR Odometry for Robotic Applications
Language:Python 226- utbm_robocar_dataset
epan-utbm / utbm_robocar_dataset
EU Long-term Dataset with Multiple Sensors for Autonomous Driving
Language:C++ 213 xingyuuchen / LIO-PPF
[IROS 2023] Fast LiDAR-Inertial Odometry via Incremental Plane Pre-Fitting and Skeleton Tracking
Language:C++ 178- Doppler-ICP
aevainc / Doppler-ICP
Official code release for Doppler ICP
Language:Python 150 Mitchell-Lee-93 / kitti-lego-loam
Easy description to run and evaluate Lego-LOAM with KITTI-data
Language:C++ 132a SLAM implementation combining FAST-LIO2 with pose graph optimization and loop closing based on LIO-SAM paper
Language:C++ 125wwenhongich / LIO-FUSION
A reinforced LiDAR inertial odometry system provides accurate and robust 6-DoF movement estimation under challenging perceptual conditions.
SRainGit / CAE-LO
CAE-LO: LiDAR Odometry Leveraging Fully Unsupervised Convolutional Auto-Encoder for Interest Point Detection and Feature Description
Language:Python 109This dataset is captured using a Velodyne VLP-16, which is mounted on an UGV - Clearpath Jackal, on Stevens Institute of Technology campus
- LiDAR-Guide
mikeroyal / LiDAR-Guide
LiDAR Guide
Language:Python 55 Easy description to run and evaluate A-LOAM with KITTI-data
Language:C++ 47yasinalm / gramme
We provide the code, pretrained models, and scripts to reproduce the experiments of the paper "Towards All-Weather Autonomous Driving". All code was implemented in Python using the deep learning framework PyTorch.
Language:Python 35- Language:C++ 29
- Language:C++ 23
[IROS 2023] Fast LiDAR-Inertial Odometry via Incremental Plane Pre-Fitting and Skeleton Tracking
Language:C++ 18jonathsch / lidar-synthesis
Official implementation of the ITSC 2023 paper "LiDAR View Synthesis for Robust Vehicle Navigation Without Expert Labels"
Language:Python 15donghwijung / LoRCoN-LO
LoRCoN-LO: Long-term Recurrent Convolutional Network-based LiDAR Odometry
Language:Python 9PawitKoch / LO-Net-pytorch
PyTorch reimplementation for "LO-Net: Deep Real-time Lidar Odometry" https://arxiv.org/abs/1904.08242
Language:Jupyter Notebook 9- Language:C++ 8
UCR-Robotics / Odometry-Benchmark
benchmark scripts for LiDAR or LiDAR-inertial odometry research
Language:Python 5- Language:Python 4
