qixuezhong Goto Github PK

a-loam

Advanced implementation of LOAM

btcdet

Behind the Curtain: Learning Occluded Shapes for 3D Object Detection

calibration_kit

ct_icp

CT-ICP: Continuous-Time LiDAR Odometry

direct_lidar_odometry

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

dsp-slam

[3DV 2021] DSP-SLAM: Object Oriented SLAM with Deep Shape Priors

fast-livo

A Fast and Tightly-coupled Sparse-Direct LiDAR-Inertial-Visual Odometry.

fast_lio

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

fast_lio_lc

The tight integration of FAST-LIO with Radius-Search-based loop closure module.

fast_lio_localization

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

fast_lio_sam

Front_end : fastlio2 Back_end : lio_sam

faster-lio

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

floam

Fast LOAM: Fast and Optimized Lidar Odometry And Mapping for indoor/outdoor localization IROS 2021

hikrobot-mvs-camera-ros

The ros driver package of Hikvision Industrial Camera SDK.

iscloam

Intensity Scan Context based full SLAM implementation for autonomous driving. ICRA 2020

kiss-icp

A LiDAR odometry pipeline that just works

lins---lidar-inertial-slam

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

lio-sam

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

lio-sam_based_relocalization

A simple system that can relocalize a robot on a built map is developed in this system. The system is based on LIO-SAM.

liv_handhold

livox_cam_simulator

A Gazebo based LiDAR-Camera Data Simulator.

ltaom

lvi-sam

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

maplab

An open visual-inertial mapping framework.

mmdetection3d

OpenMMLab's next-generation platform for general 3D object detection.

r2live

R2LIVE is a robust, real-time tightly-coupled multi-sensor fusion framework, which fuses the measurement from the LiDAR, inertial sensor, visual camera to achieve robust, accurate state estimation.

r3live

A Robust, Real-time, RGB-colored, LiDAR-Inertial-Visual tightly-coupled state Estimation and mapping package

robot_pose_ekf

The robot_pose_ekf ROS package applies sensor fusion on the robot IMU and odometry values to estimate its 3D pose.

sc-lego-loam

LiDAR SLAM: Scan Context + LeGO-LOAM

sc-lio-sam

LiDAR-inertial SLAM: Scan Context + LIO-SAM