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:
- Fast iterated Kalman filter for odometry optimization;
- Automaticaly initialized at most steady environments;
- Parallel KD-Tree Search to decrease the computation;
- Robust feature extraction;
It should be noted current version of FAST-LIO does not support Velodyne LiDAR, we may support them after March 2021.
Developers
Wei Xu 徐威: Laser mapping and pose optimization;
Zheng Liu 刘政: Features extraction.
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
Our related video: https://youtu.be/iYCY6T79oNU
Ubuntu >= 18.04.
ROS >= Melodic. ROS Installation
PCL >= 1.8, Follow PCL Installation.
Eigen >= 3.3.4, Follow Eigen Installation.
OpenCV >= 3.2, Follow openCV 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
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
....
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.
Connect to your PC to Livox Avia LiDAR following Livox-ros-driver installation, then
....
roslaunch fast_lio mapping_avia_outdoor.launch
roslaunch livox_ros_driver livox_lidar_msg.launch
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.