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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

bash 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#

bash 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#

```bash # 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#