S-FAST_LIO is a simplified implementation of FAST_LIO (Xu, Wei, et al. "Fast-lio2: Fast direct lidar-inertial odometry."), which is modified from FAST_LIO. This code is clean and accessible. It is a reference material for SLAM beginners.The main modifications are as follows:
- The Sophus is used to define the state variables, instead of the complicated IKFOM
- The gravity component is directly defined by a Vector3d, thus the complicated calculation of two-dimensional manifold can be omitted
- The code structure has been optimized, and the unnecessary codes have been deleted
- Detailed Chinese notes are added to the code
- Support for Robosense LiDAR has been added
Ubuntu >= 16.04.
PCL >= 1.8, Eigen >= 3.3.4.
Follow livox_ros_driver Installation.
We use the old version of Sophus
git clone https://github.com/strasdat/Sophus.git
cd Sophus
git checkout a621ff
mkdir build
cd build
cmake ../ -DUSE_BASIC_LOGGING=ON
make
sudo make install
Clone the repository and catkin_make:
cd ~/catkin_ws/src
git clone https://github.com/zlwang7/S-FAST_LIO.git
cd ../
catkin_make
source ~/catkin_ws/devel/setup.bash
Here we provide some additional Avia Rosbags. They are collected by Arafat-ninja.
![](pic/avia_11.png)
![](pic/avia_2.png)
![](pic/avia_1.gif)
![](pic/avia_2.gif)
Files: Can be downloaded from google drive. You can also directly use the Avia Rosbags provided by FAST_LIO (google drive).
Run:
roslaunch sfast_lio mapping_avia.launch
rosbag play YOUR_DOWNLOADED.bag
Datasets are collected by a RS-Helios LiDAR and an Xsens IMU.
![](pic/RS_indoor1.png)
![](pic/RS_indoor2.png)
![](pic/RS_indoor1.gif)
![](pic/RS_indoor2.gif)
Files: Can be downloaded from google drive.
Run:
roslaunch sfast_lio mapping_rs.launch
rosbag play YOUR_DOWNLOADED.bag
The same as FAST_LIO.
Thanks for the authors of FAST-LIO.