Skip to content

FAST_LIO_SLAM#

What is FAST_LIO_SLAM?#

  • FAST_LIO_SLAM is the integration of FAST_LIO and SC-PGO which is scan context based loop detection and GTSAM based pose-graph optimization.

Repository Information#

https://github.com/gisbi-kim/FAST_LIO_SLAM

Required Sensors#

  • LIDAR [Livox, Velodyne, Ouster]
  • IMU [6-AXIS, 9-AXIS]
  • GPS [OPTIONAL]

ROS Compatibility#

  • ROS 1

Dependencies#

  • ROS
  • PCL
  • Gtsam
wget -O ~/Downloads/gtsam.zip https://github.com/borglab/gtsam/archive/4.0.0-alpha2.zip
cd ~/Downloads/ && unzip gtsam.zip -d ~/Downloads/
cd ~/Downloads/gtsam-4.0.0-alpha2/
mkdir build && cd build
cmake ..
sudo make install

Build & Run#

1) Build#

    mkdir -p ~/catkin_fastlio_slam/src
    cd ~/catkin_fastlio_slam/src
    git clone https://github.com/gisbi-kim/FAST_LIO_SLAM.git
    git clone https://github.com/Livox-SDK/livox_ros_driver
    cd ..
    catkin_make
    source devel/setup.bash

2) Set parameters#

  • Set imu and lidar topic on Fast_LIO/config/ouster64.yaml

3) Run#

    # terminal 1: run FAST-LIO2
    roslaunch fast_lio mapping_ouster64.launch

    # open the other terminal tab: run SC-PGO
    cd ~/catkin_fastlio_slam
    source devel/setup.bash
    roslaunch aloam_velodyne fastlio_ouster64.launch

    # play bag file in the other terminal
    rosbag play xxx.bag -- clock --pause

Example Result#

Other Examples#

Acknowledgements#