《动手学深度学习》：面向中文读者、能运行、可讨论。中英文版被70多个国家的500多所大学用于教学。

Deep Learning Book Chinese Translation

PointNet and PointNet++ implemented by pytorch (pure python) and on ModelNet, ShapeNet and S3DIS.

An optimization-based multi-sensor state estimator

Release for Improved Denoising Diffusion Probabilistic Models

GTSAM is a library of C++ classes that implement smoothing and mapping (SAM) in robotics and vision, using factor graphs and Bayes networks as the underlying computing paradigm rather than sparse m…

An open source platform for visual-inertial navigation research.

pytorch implementation for "PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation" https://arxiv.org/abs/1612.00593

A ROS package tool to analyze the IMU performance.

This repository is used for automatic calibration between high resolution LiDAR and camera in targetless scenes.

This is a unofficial fork of OpenVSLAM (https://github.com/xdspacelab/openvslam)

M2DGR： a Multi-modal and Multi-scenario Dataset for Ground Robots(RA-L2021 & ICRA2022)

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

A simple method for finding the extrinsic calibration between a 3D lidar and a 6-dof pose sensor

support deepsort and bytetrack MOT(Multi-object tracking) using yolov5 with C++

Interactive Map Correction for 3D Graph SLAM

Patchwork++: Fast and robust ground segmentation method for 3D LiDAR scans. @ IROS'22

误差状态卡尔曼ESKF滤波器融合GPS和IMU，实现更高精度的定位

emoji list; emoji表情列表

A real-time multifunctional Lidar SLAM package.

A simplified implementation of FAST_LIO (with Chinese note)

ImMesh: An Immediate LiDAR Localization and Meshing Framework

LiDAR SLAM = FAST-LIO + Scan Context

(LMNet) Moving Object Segmentation in 3D LiDAR Data: A Learning-based Approach Exploiting Sequential Data (RAL/IROS 2021)

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

Display internet satellite imagery in RViz

Postgraduate Thesis: fast_lio_sam + dynamic removal (T-GRS 2024) + multi-session mapping (ICRA 2022 Kim) + object-level update + online relocalization (ICRA 2025) + real-world application (MD-LVIO)