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jkk-research / lidar_cluster_ros2

LIDAR pointcloud clustering
https://jkk-research.github.io/workshops/clustering_a/
GNU General Public License v3.0
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clustering detection formulastudent lidar ros ros2 sze szenergy

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lidar_cluster ROS 2 package

LIDAR pointcloud clustering in ROS 2 Humble

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Build this ROS 2 package

In the following ~/ros2_ws is assumed as the ROS 2 workspace:

cd ~/ros2_ws/src
git clone https://github.com/jkk-research/lidar_cluster_ros2
cd ~/ros2_ws

Build either with:

colcon build --packages-select lidar_cluster --symlink-install

or with optimized build:

MAKEFLAGS="-j4" colcon build --packages-select lidar_cluster --symlink-install --cmake-args -DCMAKE_BUILD_TYPE=Release

[!TIP] There is a detailded decription how to make this package work with ground segmentation: jkk-research.github.io/workshops/clustering_a

ROS 2 graph

graph LR;

    p[ /input_points<br/>sensor_msgs::PointCloud2]:::white --> cluster([ /cluster_node]):::light
    tf[ /tf <br/>optional topic]:::dash -.-> cluster
    cluster --> f1[ /clustered_points<br/>sensor_msgs::PointCloud2]:::white
    cluster --> f2[ /clustered_marker<br/>visualization_msgs::MarkerArray]:::white
    classDef light fill:#34aec5,stroke:#152742,stroke-width:2px,color:#152742  
    classDef dark fill:#152742,stroke:#34aec5,stroke-width:2px,color:#34aec5
    classDef white fill:#ffffff,stroke:#152742,stroke-width:2px,color:#15274
    classDef dash fill:#ffffff,stroke:#152742,stroke-width:2px,color:#15274, stroke-dasharray: 5 5
    classDef red fill:#ef4638,stroke:#152742,stroke-width:2px,color:#fff

Cluster nodes

Node Clustering Implementation Description Additional Resources
dbscan_spatial DBSCAN spatial DBSCAN non-grid implementation
dbscan_grid DBSAN grid DBSCAN voxel-grid-based implementation
dblane_spatial DBlane spatial DBlane non-grid implementation flowchart, notebooks
dblane_f1s DBlane formula DBlane formula 1 student implementation notebooks
euclidean_spatial Euclidean spatial PCL implementation of Euclidean clustering non-grid implementation PCL docs
euclidean_grid Euclidean grid PCL implementation of Euclidean clustering voxel-grid-based implementation PCL docs
Don't forget to source before ROS commands. ``` bash source ~/ros2_ws/install/setup.bash ``` 
ros2 run lidar_cluster dblane_spatial
ros2 launch lidar_cluster dblane_spatial.launch.py
ros2 launch lidar_cluster dblane_f1s.launch.py topic:=/input_points

Remarks

In VS code it is advised to add the following to include path:

${workspaceFolder}/**
/opt/ros/humble/include/**
/usr/include/pcl-1.12/**
/usr/include/eigen3/**

If you are not sure where your header files are use e.g.:

find /usr/include -name point_cloud.h
find /usr/include -name crop_box.h

Images

[!NOTE]
The following images shows two possible usage of clustering: an urban scenario and a race scenario. The first row shows a camera image that corresponds to the LIDAR image in the second row. In the third row an example is shown of the clustered LIDAR pointcloud with yellow.

Urban scenario Race scenario

Citation

If you use any of this code please consider citing the paper:

@INPROCEEDINGS{10607072,
  author={Unger, Miklós and Horváth, Ernő and Pup, Dániel and Pozna, Claudiu Radu},
  booktitle={2024 IEEE International Conference on Mobility, Operations, Services and Technologies (MOST)}, 
  title={Towards Robust LIDAR Lane Clustering for Autonomous Vehicle Perception in ROS 2}, 
  year={2024},
  pages={229-234},
  keywords={Laser radar;Lane detection;Source coding;Clustering algorithms;Robustness;Pattern recognition;Autonomous vehicles;self-driving;autonomous;point cloud;LIDAR;proceeding;filter;geometric patterns},
  doi={10.1109/MOST60774.2024.00031}}