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SI_LIO

SI_LIO is based on the Invariant-EKF theory and our code is implemented on S-FAST_LIO.

<p align="center" style="display: flex; justify-content: center;"> <img src="./img/gate_03.png" alt="drawing" width="350"/> <img src="./img/gate_03_compare.png" alt="drawing" width="350"/> </p>

Through theoretical analysis, it can be deduced that our IEKF-based estimation method achieves higher estimation accuracy compared to the Iterated EKF used in FAST-LIO2, particularly in scenarios with large IMU prediction errors. This experimental outcome corroborates our analytical conclusions.

1. Dependices

Sophus Eigen PCL livox_ros_driver

2. Build

Clone the repository and catkin_make:

cd ~/catkin_ws/src
git clone https://github.com/USTC-AIS-Lab/SI-LIO.git
cd ../
catkin_make -j
source ~/catkin_ws/devel/setup.bash

3. Run

We recommend using the M2DGR dataset.

roslaunch inva_fast_lio mapping_velodyne_m2dgr.launch
rosbag play street_04.bag

4. Acknowledgements

Thanks for the authors of S-FAST-LIO and FAST-LIO.