**FAST-LIO** (Fast LiDAR-Inertial Odometry) is a computationally efficient and robust LiDAR-inertial odometry package. It fuses LiDAR feature points with IMU data using a tightly-coupled iterated extended Kalman filter to allow robust navigation in fast-motion, noisy or cluttered environments where degeneration occurs. Our package address many key issues:
1. Fast iterated Kalman filter for odometry optimization;
2. Automaticaly initialized at most steady environments;
3. Parallel KD-Tree Search to decrease the computation;
4. Robust feature extraction;
5. Surpports for different FOV.
To know more about the details, please refer to our related paper:)
**Our related paper**: our related papers are now available on arxiv:
[FAST-LIO: A Fast, Robust LiDAR-inertial Odometry Package by Tightly-Coupled Iterated Kalman Filter](https://arxiv.org/abs/2010.05957)
Download [avia_indoor_quick_shake_example1](https://drive.google.com/file/d/1SWmrwlUD5FlyA-bTr1rakIYx1GxS4xNl/view?usp=sharing) or [avia_indoor_quick_shake_example2](https://drive.google.com/file/d/1wD485CIbzZlNs4z8e20Dv2Q1q-7Gv_AT/view?usp=sharing) and then
Download [avia_hku_main building_mapping](https://drive.google.com/file/d/1GSb9eLQuwqmgI3VWSB5ApEUhOCFG_Sv5/view?usp=sharing) and then
```
roslaunch fast_lio mapping_avia_outdoor.launch
rosbag play YOUR_DOWNLOADED.bag
```
### 4.3 High-rate rosbag (Livox Avia LiDAR sampled at 100Hz)
Download [high_rate_avia](https://drive.google.com/file/d/1UM6O3PRN3b730ZeuvKKT3yuOLNQuz8Yf/view?usp=sharing) and then
```
roslaunch fast_lio mapping_avia.launch
rosbag play YOUR_DOWNLOADED.bag
```
## 5.Acknowledgments
Thanks for LOAM(J. Zhang and S. Singh. LOAM: Lidar Odometry and Mapping in Real-time), [Livox_Mapping](https://github.com/Livox-SDK/livox_mapping) and [Loam_Livox](https://github.com/hku-mars/loam_livox).