This repository will host the official implementation of the paper:

Communication-Robust Asynchronous Distributed LiDAR Collaborative Smoothing and Mapping

multi-proxy focuses on communication-robust, asynchronous distributed and decentralized LiDAR collaborative smoothing and mapping.
The project targets multi-robot scenarios where communication is constrained, and aims to maintain consistent and accurate mapping performance.

Note that the algorithm itself does not provide odometry; you must supply your own front-end LiDAR odometry. Alternatively, you may pre-record odometry and point-cloud data from an LIO (LiDAR–Inertial Odometry) or LO (LiDAR Odometry) system.

multi-proxy subscribes to point clouds of type sensor_msgs::PointCloud2 and odometry of type nav_msgs::Odometry, and associates them into keyframes by nearest timestamps, thereby achieving complete decoupling from the front-end LiDAR odometry.

• ROS (tested with Noetic)
• gtsam (tested with 4.2.0)

  curl -L -o gtsam-4.2.0.tar.gz https://github.com/borglab/gtsam/archive/refs/tags/4.2.0.tar.gz
  tar -xzf gtsam-4.2.0.tar.gz
  rm gtsam-4.2.0.tar.gz && cd gtsam-4.2.0 && mkdir build && cd build && \
  cmake .. -DGTSAM_BUILD_WITH_MARCH_NATIVE=OFF -DGTSAM_USE_SYSTEM_EIGEN=ON -DGTSAM_USE_TBB=ON -DGTSAM_BUILD_TESTS=OFF -DGTSAM_BUILD_EXAMPLES=OFF && \
  make -j$(nproc) && make install && ldconfig

The system can be run either in a Docker environment or locally. Docker is recommended.

Install Docker and docker-compose (installation methods and URLs may change; please install them yourself and add your user to the Docker group to enable running Docker without sudo). After installation, build the image:

  docker build -t sylaranh/multi-proxy:latest .

After the image is built, you can check it using:

  docker images

To evaluate the impact of inter-robot communication quality, navigate to the docker directory and launch three containers using docker-compose. Each container represents one robot. Network delay, packet loss, and bandwidth constraints are automatically injected between containers via net_work_loss_robot_0.sh.

  xhost +
  cd <your_workspace>/src/multi_proxy/docker/
  docker-compose up

Start ROS Master (Host)

Start roscore on the host machine:

  roslaunch src/multi_proxy/launch/multi_s3e_master.launch

Launch Robots in Docker Containers Open a new terminal and enter the multi-proxy0 container:

  docker exec -it multi-proxy0 bash
  cd ws_code
  catkin_make
  source devel/setup.bash
  roslaunch multi_proxy multi_s3e0.launch

Open another terminal and enter the multi-proxy1 container:

  docker exec -it multi-proxy1 bash
  cd ws_code
  catkin_make
  source devel/setup.bash
  roslaunch multi_proxy multi_s3e1.launch

Open another terminal and enter the multi-proxy2 container:

  docker exec -it multi-proxy2 bash
  cd ws_code
  catkin_make
  source devel/setup.bash
  roslaunch multi_proxy multi_s3e2.launch

Using Pre-recorded Odometry and Pointcloud

rosbag play S3E_College_robot_odom.bag

If Single robot LIO is not configured, instead use a merged single-robot odometry dataset that has been precomputed (e.g., using FastLIO). Typical topics include: /robot_0/odometry /robot_0/cloud_deskewed

A common workflow is: Play each robot’s dataset independently. Add robot name prefixes to the odometry and cloud topics. Merge all robots’ lio output into a single rosbag.

If you find this work useful in your research, please consider citing:

@ARTICLE{11358654,
  author={Wang, Jiancheng and Cai, Chenyuan and Tan, JinQian and Chen, Haoyao},
  journal={IEEE Robotics and Automation Letters}, 
  title={Communication-Robust Asynchronous Distributed LiDAR Collaborative Smoothing and Mapping}, 
  year={2026},
  volume={},
  number={},
  pages={1-8},
  keywords={Robots;Collaboration;Optimization;Location awareness;Laser radar;Simultaneous localization and mapping;Robustness;Point cloud compression;Pipelines;Trajectory;C-LSLAM;Multi-Robot;Asynchronous;Distributed;Decentralized;Collaborative Localization},
  doi={10.1109/LRA.2026.3655282}
}

• 📄 Paper accepted
• 🚧 Datasets is under preparation