# FD-SLAM

## 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.

### Original Repository link

[https://github.com/SLAMWang/FD-SLAM](<https://github.com/SLAMWang/FD-SLAM>)

### Required Sensors

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

### ROS Compatibility

- ROS 1

### Dependencies

- [ROS](<http://wiki.ros.org/noetic/Installation/Ubuntu>)
- [PCL](<https://pointclouds.org/downloads/#linux>)
- [g2o](<http://wiki.ros.org/g2o>)
- [Suitesparse](<https://github.com/DrTimothyAldenDavis/SuiteSparse>)

The following ROS packages are required:

- geodesy
- nmea\_msgs
- pcl\_ros
- [ndt\_omp](<https://github.com/koide3/ndt_omp>)
- [U\_gicp](<https://github.com/SLAMWang/UGICP>) This is modified based on [fast\_gicp](<https://github.com/koide3/fast_gicp>) by us. We use UGICP for keyframe matching.

## Build &amp; Run

### 1\) Build

```bash
cd ~/catkin_ws/src
git clone https://github.com/SLAMWang/FD-SLAM.git
cd ..
catkin_make
```

### 2\) Services

```bash
/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

```bash
source devel/setup.bash
roslaunch hdl_graph_slam hdl_graph_slam_400_ours.launch
```