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What is FD-SLAM?#

  • FD_SLAM is Feature&Distribution-based 3D LiDAR SLAM method based on Surface Representation Refinement. In this algorithm novel feature-based Lidar odometry used for fast scan-matching, and used a proposed UGICP method for keyframe matching.

Repository Information#

This is an open source ROS package for real-time 6DOF SLAM using a 3D LIDAR.

It is based on hdl_graph_slam and the steps to run our system are same with hdl-graph-slam.

Required Sensors#

  • LIDAR[VLP-16, HDL-32, HDL-64, OS1-64]
  • GPS
  • IMU [Optional]

ROS Compatibility#

  • ROS 1


The following ROS packages are required:

  • geodesy
  • nmea_msgs
  • pcl_ros
  • ndt_omp
  • U_gicp This is modified based on fast_gicp by us. We use UGICP for keyframe matching.

Build & Run#

1) Build#

cd ~/catkin_ws/src
git clone
cd ..

2) Services#

/hdl_graph_slam/dump  (hdl_graph_slam/DumpGraph)
  - save all the internal data (point clouds, floor coeffs, odoms, and pose graph) to a directory.

/hdl_graph_slam/save_map (hdl_graph_slam/SaveMap)
  - save the generated map as a PCD file.

3) Set parameters#

  • All the configurable parameters are listed in launch/****.launch as ros params.

4) Run#

source devel/setup.bash
roslaunch hdl_graph_slam hdl_graph_slam_400_ours.launch