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[IROS2022] Robust Real-time LiDAR-inertial Initialization Method.
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## Robust Real-time LiDAR-inertial Initialization
**LI-Init** is a robust, real-time initialization method for LiDAR-inertial system. The proposed method calibrates the temporal offset and extrinsic parameter between LiDARs and IMUs, and also the gravity vector and IMU bias. Our method does not require any target or extra sensor, specific structured environment, prior environment point map or initial values of extrinsic and time offset. Our package address following key issues:
1. A robust LiDAR odometry (**FAST-LO**) modified from FAST-LIO2.
2. Fast and robust **temporal offset and extrinsic parameter calibration** between LiDAR and IMU without any hardware setup.
3. Support **multiple LiDAR types**: both mechanical spinning LiDAR (Hesai, Velodyne, Ouster) and solid-state LiDAR ( Livox Avia/Mid360)
4. Seamlessly merged into FAST-LIO2, as a robust initialization module.
**Contributors**: [Fangcheng Zhu 朱方程](https://github.com/zfc-zfc)， [Yunfan Ren 任云帆](https://github.com/RENyunfan)， [Wei Xu 徐威](https://github.com/XW-HKU)， [Yixi Cai 蔡逸熙](https://github.com/Ecstasy-EC)
### Pipeline
<div align="center"><img src="image/pipeline.png" width=100% /></div>
### Excite the Sensors
<div align="center"><img src="image/Excitation.gif" width=100% /></div>
### Related Paper
our related papers are now available: [Robust Real-time LiDAR-inertial Initialization](https://ieeexplore.ieee.org/document/9982225)
If our code is used in your project, please cite our paper following the bibtex below:
```
@inproceedings{zhu2022robust,
title={Robust real-time lidar-inertial initialization},
author={Zhu, Fangcheng and Ren, Yunfan and Zhang, Fu},
booktitle={2022 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)},
pages={3948--3955},
year={2022},
organization={IEEE}
}
```
### Related Video:
our accompanying videos are now available on **YouTube** (click below images to open) and [Bilibili](https://www.bilibili.com/video/BV1ZS4y127mW?spm_id_from=333.337.search-card.all.click).
<div align="center">
<a href="https://www.youtube.com/watch?v=WiHgcPpKwvU" target="_blank">
<img src="image/video_cover.png" width=70% />
</div>
## 1. Prerequisites
### 1.1 **Ubuntu** and **ROS**
Ubuntu >= 18.04.
ROS >= Melodic. [ROS Installation](http://wiki.ros.org/ROS/Installation)
### 1.2. **PCL && Eigen**
PCL >= 1.8, Follow [PCL Installation](http://www.pointclouds.org/downloads/linux.html).
Eigen >= 3.3.4, Follow [Eigen Installation](http://eigen.tuxfamily.org/index.php?title=Main_Page).
### 1.3. **livox_ros_driver**
Follow [livox_ros_driver Installation](https://github.com/Livox-SDK/livox_ros_driver).
*Remarks:*
- Since the **LI_Init** must support Livox serials LiDAR firstly, so the **livox_ros_driver** must be installed and **sourced** before run any LI_Init luanch file.
- How to source? The easiest way is add the line `source $Livox_ros_driver_dir$/devel/setup.bash` to the end of file `~/.bashrc`, where `$Livox_ros_driver_dir$` is the directory of the livox_ros_driver workspace (should be the `ws_livox` directory if you completely followed the livox official document).
### **1.4. ceres-solver**
Our code has been tested on [ceres-solver-2.0.0](http://ceres-solver.org/installation.html#linux). Please download ceres-solver following the instructions.
### **1.5. Getting start with Docker**
When you use Docker, you could solve the prerequisites above at once.
For more information, you can check [docker_start.md](./docker/docker_start.md).
## 2. Build
Clone the repository and catkin_make:
```
cd ~/catkin_ws/src
git clone https://github.com/hku-mars/LiDAR_IMU_Init.git
cd ..
catkin_make -j
source devel/setup.bash
```
## 3. Run Your Own Data
**Please make sure the unit of your input angular velocity is rad/s.** If it is degree/s, please refer to https://github.com/hku-mars/LiDAR_IMU_Init/issues/43.
**Please make sure the parameters in config/xxx.yaml are correct before running the projecExcerpt of 9,224 characters
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TaeYoung Kim · Robotics Lab, Hyundai Motor Company · South Korea
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