LiDAR SLAM

• Introduction and contents
• Core SLAM lib
  • Dependencies
  • Installation
• ROS wrapping
  • Dependencies
  • Installation
  • Usage
• ParaView wrapping
  • Dependencies
  • Installation
  • Usage
  • Use SLAM in LidarView

Introduction and contents

This repo contains LiDAR-only visual SLAM developped by Kitware, as well as ROS and ParaView wrappings for easier use.

It has been successfully tested on data from several common LiDAR sensors:

• Velodyne (VLP-16, VLP-32c, HDL-32, HDL-64, VLS-128)
• Ouster (OS0/1/2-32/64/128)
• RoboSense (RS-LiDAR-16 RS-LiDAR-32)
• Hesai (PandarXT16, PandarXT32, Pandar128)

Have a look at our SLAM demo video!

This codebase is under active development. If you're interested by new features, new sensors' support or any project that could be using this SLAM, do not hesitate to contact us at [email protected].

Repo contents :

• slam_lib/ : core LidarSlam library containing SLAM algorithm and other utilities.
• superbuild/ : Cross-platform installer.
• ros_wrapping/ : ROS packages to enable SLAM use on a ROS system.
• paraview_wrapping/ : ParaView plugin to enable SLAM use with ParaView/LidarView.
• ci/ : continuous integration files to automatically build and check LidarSlam lib.
• CMakeLists.txt : CMakeLists used to call to build core LidarSlam lib and paraview_wrapping.

Core SLAM lib

Dependencies

Dependencies are listed in the table below along with the version used during development and testing. Minimum required versions have not been determined yet.

Dependency	Minimum tested Version
Eigen3	3.3.4
Ceres	1.13.0
PCL	1.8
nanoflann	1.3.0
g2o*	1.0.0 (master)
OpenMP*	2.0
gtsam*	4.2a8
OpenCV*	4.5.4

(*) optional dependencies :

• If G2O is not available (or disabled), LidarSlam lib will still be compiled, but without pose graph optimization features.
• If GTSAM is not available (or disabled), LidarSlam lib will still be compiled, but without IMU processing features.
• If OpenCV is not available (or disabled), LidarSlam lib will still be compiled, but without camera features.
• If OpenMP is available, it is possible to use multi-threading to run some SLAM steps in parallel and achieve higher processing speed.
• If OpenCV is not available (or disabled), LidarSlam lib will still be compiled, but without camera integration.

/!\ Warning Make sure to compile/install G2O with the same Ceres version as the one used in the SLAM compilation. To do so, disable the feature G2O_USE_VENDORED_CERES during G2O compilation and link against the right version of Ceres.

Installation

The LidarSlam lib has been tested on Linux, Windows and OS X.

First, got to your workspace directory and clone the SLAM repository.

git clone https://gitlab.kitware.com/keu-computervision/slam.git src --recursive

With system dependencies

To build only LidarSlam lib using your system dependencies, run :

mkdir build && cd build
cmake ../src -DCMAKE_BUILD_TYPE=Release
cmake --build . -j

NOTE : On Windows, if some dependencies were installed using vcpkg, the variable CMAKE_TOOLCHAIN_FILE must be specified : cmake ../src -DCMAKE_BUILD_TYPE=Release -DCMAKE_TOOLCHAIN_FILE=[vcpkg-install]/scripts/buildsystems/vcpkg.cmake

With local dependencies

You can link to the local libraries you have installed adding cmake flags. Notably with Ceres and G2O:

cmake ../src -DCMAKE_BUILD_TYPE=Release -DCeres_DIR=path/to/CeresConfig.cmake -Dg2o_DIR=path/to/g2oConfig.cmake

With Superbuild

In your workspace, run :

mkdir build && cd build
cmake ../src/slam-superbuild -DCMAKE_BUILD_TYPE=Release
cmake --build . -j

NOTE: By default in the superbuild, mandatory dependencies are installed but optional dependencies are not. You can decide which dependencies to install with the superbuild using the options INSTALL_XX. For example, to not build PCL:

cmake ../src/slam-superbuild -DCMAKE_BUILD_TYPE=Release -DINSTALL_PCL=OFF

Note that installing and enabling an optional dependency is not the same. If you want to install and enable the use of an optional dependency you need to switch two variables to ON : INSTALL_XX and ENABLE_XX.

Example for GTSAM :

cmake ../src/slam-superbuild -DCMAKE_BUILD_TYPE=Release -DINSTALL_GTSAM=ON -DENABLE_GTSAM=ON

More documentation about the superbuild can be found here.

ROS wrapping

The ROS wrapping has been tested on Linux only.

Dependencies

Ensure all LidarSlam dependencies are respected. Specific ROS packages dependencies are listed in the table below along with the version used during development and testing.

Dependency	Tested Versions	Install (sudo apt-get install <pkg>)	status
ROS	melodic, noetic	ros-$ROS_DISTRO-desktop-full and tutorial	mandatory
pcl-ros	1.7.4	ros-$ROS_DISTRO-pcl-ros	mandatory
geodesy	0.5.3	ros-$ROS_DISTRO-geodesy	mandatory
gps_common	0.3.0	ros-$ROS_DISTRO-gps-common	optionnal
apriltag	3.2.0	ros-$ROS_DISTRO-apriltag	optionnal
g2o	5.3	ros-$ROS_DISTRO-libg2o	optionnal

For Velodyne usage, please note that the ROS Velodyne driver with minimum version 1.6 is needed. Be careful, this ROS Velodyne driver 1.6 is not backward-compatible with previous versions. If you're running on Ubuntu 20 / ROS Noetic, you can install the new Velodyne driver using the command sudo apt install ros-noetic-velodyne ros-noetic-velodyne-pcl. If running on previous versions of Ubuntu/ROS (18/Melodic and below), you need to compile this driver from source : just clone the git repo in your catkin worskpace sources, it will be automatically built with next catkin_make or catkin build.

For Ouster usage, the driver can be found in this git repo

Installation

Clone this git repo directly into your catkin workspace (called catkin_ws in the following), under the src directory

mkdir catkin_ws && cd catkin_ws
git clone https://gitlab.kitware.com/keu-computervision/slam.git src/slam --recursive

NOTE : Boost, g2o and PCL dependencies can be resolved wih ROS packages. WARNING : Be sure to use the same PCL library dependency for ROS basic tools and slam library to avoid compilation errors and/or segfaults.

With system dependencies

Run catkin_make --cmake-args -DCMAKE_BUILD_TYPE=RelWithDebInfo or catkin_make --cmake-args -DCMAKE_BUILD_TYPE=Release (to turn on optimizations, highly recommended when using Eigen). The same can be done with catkin build. By default, this will build LidarSlam lib before ROS packages. If you want to use your system LidarSlam, you need to set the cmake variable BUILD_SLAM_LIB to OFF : catkin_make --cmake-args -DCMAKE_BUILD_TYPE=Release -DBUILD_SLAM_LIB=OFF

With local dependencies

As with Core SLAM lib, you can use local dependencies for Slam lib by passing them to catkin.

Example for Ceres and g2o :

catkin_make -j --cmake-args -DCMAKE_BUILD_TYPE=Release  -DCeres_DIR=path/to/CeresConfig.cmake -Dg2o_DIR=path/to/g2oConfig.cmake
 OR
catkin build -j --cmake-args -DCMAKE_BUILD_TYPE=Release -DCeres_DIR=path/to/CeresConfig.cmake -Dg2o_DIR=path/to/g2oConfig.cmake

If you want to use a local version of LidarSlam library you can specify to the package not to build it and supply the path to the LidarSlam cmake file :

catkin build -j --cmake-args -DCMAKE_BUILD_TYPE=Release -DBUILD_SLAM_LIB=OFF -DLidarSlam_DIR=path/to/LidarSlam.cmake

With Superbuild

The superbuild can also download and install the required dependencies.

WARNING It is not possible to use PCL from the superbuild (this would create runtime issues with system version).

WARNING The superbuild must be installed outside of catkin workspace.

Example in parent directory of your catkin workspace (e.g. catkin_ws/..) :

# Build Superbuild
mkdir SB-build && cd SB-build
cmake ../catkin_ws/src/slam/slam-superbuild -GNinja -DCMAKE_BUILD_TYPE=Release -DINSTALL_PCL=OFF
cmake --build . -j
# Build Slam ROS package
cd ../catkin_ws
catkin_make -j --cmake-args -DCMAKE_BUILD_TYPE=Release -DSUPERBUILD_INSTALL_DIR=absolute/path/to/superbuild/install
 OR
catkin build -j --cmake-args -DCMAKE_BUILD_TYPE=Release -DSUPERBUILD_INSTALL_DIR=absolute/path/to/superbuild/install

The default behavior is that the ROS wrapping builds the SLAM library, but the superbuild can also install the SLAM library. It is possible to use the superbuild one by setting the BUILD_SLAM_SHARED_LIB variable to ON in superbuild build and BUILD_SLAM_LIB to OFF in ROS wrapping build.

Example :

mkdir SB-build && cd SB-build
cmake ../catkin_ws/src/slam/slam-superbuild -GNinja -DCMAKE_BUILD_TYPE=Release -DINSTALL_PCL=OFF -DBUILD_SLAM_SHARED_LIB=ON
cmake --build . -j
cd ../catkin_ws
catkin build -j --cmake-args -DCMAKE_BUILD_TYPE=Release -DSUPERBUILD_INSTALL_DIR=absolute/path/to/superbuild/install -DBUILD_SLAM_LIB=OFF

### Live usage

For Velodyne :
```bash
roslaunch lidar_slam slam_velodyne.launch use_sim_time:=false
roslaunch lidar_slam slam_velodyne.launch use_sim_time:=false gps:=true   # if GPS/SLAM calibration has to be run

For Ouster :

roslaunch lidar_slam slam_ouster.launch replay:=false
roslaunch lidar_slam slam_ouster.launch replay:=false gps:=true   # if GPS/SLAM calibration has to be run

See ros_wrapping/lidar_slam/README.md for more details.

ParaView wrapping

The LidarSlamPlugin Paraview wrapping has been tested on Linux, Windows and OS X.

Dependencies

Ensure all LidarSlam dependencies are respected. Specific dependencies are listed in the table below along with the version used during development and testing.

Dependency	Tested Version
ParaView	5.4, 5.6 and 5.9

Be careful to use and link to the same libraries as ParaView/LidarView's (especially with VTK, Eigen, PCL, Ceres, nanoflann, etc.). Otherwise, if different flags or modules were enabled, some troubles may arise at build time, or it could lead to version mismatch and segfault at runtime.

For example, if PCL is built with pcl_visualization module, it must link to the same VTK than the one used by ParaView.

Installation

To build LidarSlam lib and this ParaView plugin LidarSlamPlugin, just cd to this repo root dir and run :

mkdir build
cd build
cmake .. -DCMAKE_BUILD_TYPE=RelWithDebInfo -DSLAM_PARAVIEW_PLUGIN:BOOL=ON
cmake --build . -j

Set XX_DIR variables to the same path dependencies of ParaView/LidarView when they exist (Eigen, Ceres, nanoflann, etc...).

Usage

• Open ParaView
• Tools tab > Manage Plugins > Load New
• Browse to the <install>/lib/ dir and select libLidarSlamPlugin.so or LidarSlamPlugin.dll
• Load LiDAR frames and LiDAR calibration to use
• Select the frames in the Pipeline Browser, instantiate a SLAM filter, and apply it.

Currently, all features are not available in ParaView plugin. Features such as GPS/LiDAR calibration, pose graph optimization or temporal logging are only supported in ROS wrapping. However, ParaView plugin is useful to play with SLAM, interactively try out parameters, visualize and export results.

Use SLAM in LidarView

This LidarSlamPlugin is natively included in LidarView. For more detailed information on how to enable and use SLAM filter in LidarView, see paraview_wrapping/Plugin/doc/How_to_SLAM_with_LidarView.md.

Pre-built binaries of LidarView with this SLAM plugin are available for download here.