hit-ygq / eskf_lio Goto Github PK

This repository is a modified LiDAR-inertial odometry system. The system is developed based on the open-source odometry framework FAST-LIO to get the odometry information. And the feature extract moudle is implemented based on LIO-SAM .

• Feature extract moudle is implemented based on lio-sam, this moudle support multiple lidar types(such as velodyne,ouster,robosense, livox etc.);
• laser mapping moudle is implemented base on fast-lio 1.0, Use Eigen matrix instead of IKFom;
• use ikdtree manage the map;
• the new laser mapping moudle support multiple lidar types: both traditional spinning lidar (velodyne, ouster, robsense etc.) and solid-state lidar(livox);
• add online extrinsic calib as fast-lio2
• add new lidar process moudle, this moudle support process multi-lidar (as one Lidar);

[update 2022-08-05]

UrbanNav-HK-TST-20210517 test video

Ouster32 test video

hkust_20201105full test video

Follow the fast_lio

Use the following commands to download and compile the package.

cd ~/${yourdir}/src
git clone https://github.com/chengwei0427/ESKF_LIO.git
cd ..
source devel/setup.bash
catkin_make 

1. change the params in config/feat.yaml;
2. test direct/feature based eskf-lio use run.launch;
3. test multi-lidar slam use run_multi.launch;

1. you cloud test the multi-lidar with the UrbanNavDataset;
2. the auxiliary lidar only support velodyne current, the primary lidar support multi-type lidars(such as velodyne,ouster,robosense, livox etc.);

• add ivox
• add extrinsic parameter calibration
• compare with FAST-LIO2
• add test video
• support multi-lidar

Thanks for LOAM, FAST_LIO ,LIO_SAM and UrbanNavDataset.