Noted: Ubuntu 16.04 and lower is not supported

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;

Related video:

FAST-LIO2

FAST-LIO1

New features:

1. Incremental mapping using ikd-Tree, achieve faster speed and over 100Hz LiDAR rate.
2. Direct odometry on Raw LiDAR points (feature extraction can be closed), achieving better accuracy.
3. Since no need for feature extraction, FAST-LIO2 can support different LiDAR Types including spinning (Velodyne, Ouster) and solid-state (Avia, horizon) LiDARs. And most of LiDARs can be easily supported.
4. Support external IMU.
5. Support ARM-based platforms including Khadas VIM3, Nivida TX2, Raspberry 4B with 8G RAM.

Contributors

Wei Xu 徐威，Yixi Cai 蔡逸熙，Dongjiao He 贺东娇，Fangcheng Zhu 朱方程，Jiarong Lin 林家荣，Zheng Liu 刘政

To know more about the details, please refer to our related paper:)

Related papers:

our related papers are now available on arxiv:

FAST-LIO2: Fast Direct LiDAR-inertial Odometry (Currently Uavailable)

FAST-LIO: A Fast, Robust LiDAR-inertial Odometry Package by Tightly-Coupled Iterated Kalman Filter

Ubuntu >= 18.04 (Ubuntu 16.04 is not supported)

ROS >= Melodic. ROS Installation

PCL >= 1.8, Follow PCL Installation.

Eigen >= 3.3.4, Follow Eigen Installation.

Follow livox_ros_driver Installation.

Clone the repository and catkin_make:

    cd ~/catkin_ws/src
    git clone https://github.com/XW-HKU/fast_lio.git
    git submodule update --init
    cd ..
    catkin_make
    source devel/setup.bash

Remarks:

• If you want to use a custom build of PCL, add the following line to ~/.bashrc export PCL_ROOT={CUSTOM_PCL_PATH}

Connect to your PC to Livox Avia LiDAR by following Livox-ros-driver installation, then

    ....
    cd ~/catkin_ws
    roslaunch fast_lio mapping_avia.launch
    roslaunch livox_ros_driver livox_lidar_msg.launch
    

Remarks:

• If you want to change the frame rate, please modify the publish_freq parameter in the livox_lidar_msg.launch of Livox-ros-driver before make the livox_ros_driver pakage.

Download avia_indoor_quick_shake_example1 or avia_indoor_quick_shake_example2 and then

roslaunch fast_lio mapping_avia.launch
rosbag play YOUR_DOWNLOADED.bag

Download avia_hku_main building_mapping and then

roslaunch fast_lio mapping_avia_outdoor.launch
rosbag play YOUR_DOWNLOADED.bag

In order to validate the robustness and computational efficiency of FAST-LIO in actual mobile robots, we build a small-scale quadrotor which can carry a Livox Avia LiDAR with 70 degree FoV and a DJI Manifold 2-C onboard computer with a 1.8 GHz Intel i7-8550U CPU and 8 G RAM, as shown in below.

Thanks for LOAM(J. Zhang and S. Singh. LOAM: Lidar Odometry and Mapping in Real-time), Livox_Mapping and Loam_Livox.