# IA-LIO-SAM

## What is IA-LIO-SAM?

- IA\_LIO\_SLAM is created for data acquisition in unstructured environment and it is a framework for Intensity and Ambient Enhanced Lidar Inertial Odometry via Smoothing and Mapping that achieves highly accurate robot trajectories and mapping.

## Repository Information

### Original Repository link

[https://github.com/minwoo0611/IA\_LIO\_SAM](<https://github.com/minwoo0611/IA_LIO_SAM>)

### Required Sensors

- LIDAR \[Velodyne, Ouster\]
- IMU \[9-AXIS\]
- GNSS

### ROS Compatibility

- ROS 1

### Dependencies

- [ROS](<http://wiki.ros.org/ROS/Installation>) (tested with Kinetic and Melodic)

  - `for ROS melodic:`

    ```bash
    sudo apt-get install -y ros-melodic-navigation
    sudo apt-get install -y ros-melodic-robot-localization
    sudo apt-get install -y ros-melodic-robot-state-publisher
    ```

  - `for ROS kinetic:`

    ```bash
    sudo apt-get install -y ros-kinetic-navigation
    sudo apt-get install -y ros-kinetic-robot-localization
    sudo apt-get install -y ros-kinetic-robot-state-publisher
    ```

- [GTSAM](<https://github.com/borglab/gtsam/releases>) (Georgia Tech Smoothing and Mapping library)

  ```bash
  wget -O ~/Downloads/gtsam.zip https://github.com/borglab/gtsam/archive/4.0.2.zip
  cd ~/Downloads/ && unzip gtsam.zip -d ~/Downloads/
  cd ~/Downloads/gtsam-4.0.2/
  mkdir build && cd build
  cmake -DGTSAM_BUILD_WITH_MARCH_NATIVE=OFF ..
  sudo make install -j8
  ```

## Build &amp; Run

### 1\) Build

```bash
    mkdir -p ~/catkin_ia_lio/src
    cd ~/catkin_ia_lio/src
    git clone https://github.com/minwoo0611/IA_LIO_SAM
    cd ..
    catkin_make
```

### 2\) Set parameters

- After downloading the repository, change topic and sensor settings on the config file (`workspace/src/IA_LIO_SAM/config/params.yaml`)

- For imu-lidar compatibility, extrinsic matrices from calibration must be changed.

- To enable autosave, `savePCD` must be `true` on the `params.yaml` file (`workspace/src/IA_LIO_SAM/config/params.yaml`).

### 3\) Run

```
  # open new terminal: run IA_LIO
  source devel/setup.bash
  roslaunch lio_sam run.launch

  # play bag file in the other terminal
  rosbag play RECORDED_BAG.bag --clock
```

## Sample dataset images

## Example dataset

Check original repo link for example dataset.

## Contact

- Maintainer: Kevin Jung (`GitHub: minwoo0611`)

## Paper

Thank you for citing [IA-LIO-SAM](<https://github.com/minwoo0611/IA_LIO_SAM/blob/master/config/doc/KRS-2021-17.pdf>) if you use any of this code.

```bibtex
@article{jung2021intensity,
  title={Intensity and Ambient Enhanced Lidar-Inertial SLAM for Unstructured Construction Environment},
  author={Jung, Minwoo and Jung, Sangwoo and Jang, Hyesu and Kim, Ayoung},
  journal={The Journal of Korea Robotics Society},
  volume={16},
  number={3},
  pages={179--188},
  year={2021},
  publisher={Korea Robotics Society}
}
```

Part of the code is adapted from [LIO-SAM (IROS-2020)](<https://github.com/TixiaoShan/LIO-SAM>).

```bibtex
@inproceedings{legoloam2018shan,
  title={LeGO-LOAM: Lightweight and Ground-Optimized Lidar Odometry and Mapping on Variable Terrain},
  author={Shan, Tixiao and Englot, Brendan},
  booktitle={IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)},
  pages={4758-4765},
  year={2018},
  organization={IEEE}
}
```

## Acknowledgements

- IA-LIO-SAM is based on LIO-SAM (T. Shan, B. Englot, D. Meyers, W. Wang, C. Ratti, and D. Rus. LIO-SAM: Tightly-coupled Lidar Inertial Odometry via Smoothing and Mapping).