ROS 2 support of GroundGrid: dcmlr/groundgrid.
Paper: GroundGrid: LiDAR Point Cloud Segmentation and Terrain Estimation; IEEE'2024
- ROS 2 Humble
rosdep update
rosdep install -y --from-paths . --ignore-src --rosdistro $ROS_DISTRO
colcon build --symlink-install --cmake-args -DCMAKE_BUILD_TYPE=Release
source install/setup.bash
ros2 launch groundgrid groundgrid.launch.xml
Download Semantic KITTI Dataset.
Downloaded dataset structure is as follows:
ros-groundgrid
├── data
│ └── kitti
│ ├── dataset
│ | └── sequences
| │ ├── 00
│ │ │ ├── calib.txt
│ │ │ ├── labels
│ │ │ ├── poses.txt
│ │ │ ├── times.txt
│ │ │ └── velodyne
│ │ ├── 01
...
ros-humble-rosbag2-storage-mcap
is required to serialize bag files into MCAP format.
sudo apt install ros-humble-rosbag2-storage-mcap
Run kitti2bag.py
to convert dataset to bag file in mcap format:
python3 scripts/kitti2bag.py </KITTI/DATASET/PATH>
For example in the above case:
python3 scripts/kitti2bag.py ./data/kitti/dataset
In order to convert the particular sequence, please specify -s <SEQUENCE_NUMBER>
:
python3 scripts/kitti2bag.py </KITTI/DATASET/PATH> -s 00
After finishing conversion, you can run the recorded bag file as below:
ros2 bag play -s mcap </KITTIT/BAG/DIR>
Bag files will be saved into data/kitti_bag/semantic_kitti_<SEQUENCE>
by default:
ros2 bag play -s mcap ./data/kitti_bag/semantic_kitti_00
For visualization, rviz/groundgrid.rviz
is prepared for the rviz configuration by default:
rviz2 -d ./rviz/groundgrid.rviz