This repo is based on the LeGO-LOAM-BOR , and has been modified for ground vehicles. We did not fork the repo due to significant modifications, variant features and frameworks are implemented.

The original authors deserve all the credits, we just stand on the shoulders of giants.

The following features are provided and are different from original version:

• ROS2 version (Humble) of LeGO LOAM BOR, support online and offline(bag) mapping, IMU/Odometry is optional.
• Pose graph visualization.
• Conditional loop closure mechanism for a more stable mapping result.
• The result is saved as a pose graph, users can leverage our pose graph editor to modify the result ex: manual loop closure.
• Our pose graph editor allow users to merge two pose graphs.
• The pose graph can be used in DDDMR MCL localization.

Watch more videos on Youtube of 3D navigation stack -> DDDMobilerobot channel.

The package runs in the docker, so we need to build the image first. We support both x64 (tested in intel NUC) and arm64 (tested in nvidia jetson jpack6).

cd ~
git clone https://github.com/dddmobilerobot/dddmr_navigation.git
cd ~/dddmr_navigation && git submodule update --init dddmr_docker src/dddmr_lego_loam_bor src/dddmr_rviz_tools
cd ~/dddmr_navigation/dddmr_docker/docker_file && ./build.bash

To play SLAM, you will need to download bag file (4.0GB). To play pose graph editor, you will need to download pose graph folder (2.6MB).

cd ~/dddmr_navigation/src/dddmr_lego_loam_bor && ./download_files.bash

cd ~/dddmr_navigation/dddmr_docker && ./run_demo.bash

cd ~/dddmr_navigation && source /opt/ros/humble/setup.bash && colcon build --symlink-install --cmake-args -DCMAKE_BUILD_TYPE=Release
source install/setup.bash
ros2 launch lego_loam_bor lego_loam_bag.launch

cd ~/dddmr_navigation && source /opt/ros/humble/setup.bash && colcon build --symlink-install --cmake-args -DCMAKE_BUILD_TYPE=Release
source install/setup.bash
ros2 launch lego_loam_bor pose_graph_editor.launch

Many thanks to LeGO-LOAM paper:

@inproceedings{legoloam2018,
  title={LeGO-LOAM: Lightweight and Ground-Optimized Lidar Odometry and Mapping on Variable Terrain},
  author={Tixiao Shan and Brendan Englot},
  booktitle={IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)},
  pages={4758-4765},
  year={2018},
  organization={IEEE}
}

Press "shift" and select a pose, the selected key frame will be red

Select a pose without press any key, the selected key frame will be green

The buttons px+, px-, py+, py-, .... are used to fine tune the icp result. When the result is satified, click "Accept", an edge will be added

Tick the second radio button so you will be able to work on the second pose graph. All operations will be activated on the second pose graph.

The Merge ICP button will match the first key frame of each pose graph. i.e.: Merge red key frame of the first pose graph and the red key frame of the second pose graph. After click accept merge, there will be a pop up window to ask thenew directory to save the merged result. Once the result is saved, you can go back to pose graph panel to keep working on the merge result. Steps:

1. Switch to the first pose graph, and pressed "shift" to select the first key frame of pose graph 1.
2. Switch to the second pose graph, and pressed "shift" to select the first key frame of pose graph 2.
3. Tick Merge visualization on the Rviz, then you will see two key frames. You can ICP them and fine tune the result.
4. Click accpet to save the result.