himhan34 / LOG-LIO-for-sping-lidar

A LiDAR-Inertial Odometry with Efficient Local Geometric Information Estimation

LOG-LIO

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Our recent work LOG-LIO2 is now available!

The trajectory file will be saved in TUM format in the file named "/Log/target_path.txt".

And a more detailed readme is coming soon!

Related video: Ring FALS.

1. Prerequisites

1.1 Ubuntu and ROS

Ubuntu >= 16.04

For Ubuntu 18.04 or higher, the default PCL and Eigen is enough for FAST-LIO to work normally.

1.2 Ring FALS Normal Estimator

Compile follow Ring FALS normal estimator.

2. Build

Clone the repository and catkin_make:

    cd ~/$A_ROS_DIR$/src
    git clone https://github.com/tiev-tongji/LOG-LIO.git
    cd ..
    catkin_make
    source devel/setup.bash

3. run

We conduct experiments on the M2DGR and NTU VIRAL datasets. The corresponding launch and yaml file is provided.

Note that the timestamp in the NTU VARIL dataset is the end time.

    cd ~/$LOG_LIO_ROS_DIR$
    source devel/setup.bash
    # for the M2DGR dataset
    roslaunch log_lio mapping_m2dgr.launch
    # for the NTU VIRAL dataset
    roslaunch log_lio mapping_viral.launch

4. Acknowledgments

Thanks for LOAM(J. Zhang and S. Singh. LOAM: Lidar Odometry and Mapping in Real-time), Fast-LIO2, ikd-Tree and VoxelMap.

Citation

    @article{huang2023log,
    title={LOG-LIO: A LiDAR-Inertial Odometry with Efficient Local Geometric Information Estimation},
    author={Huang, Kai and Zhao, Junqiao and Zhu, Zhongyang and Ye, Chen and Feng, Tiantian},
    journal={IEEE Robotics and Automation Letters},
    volume={9},
    number={1},
    pages={459--466},
    year={2023},
    publisher={IEEE}
    }