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co_lrio package from co-lrio repo

co_lrio

Package Summary

Tags No category tags.
Version 1.0.0
License TODO
Build type AMENT_CMAKE
Use RECOMMENDED

Repository Summary

Checkout URI https://github.com/zhongshp/co-lrio.git
VCS Type git
VCS Version master
Last Updated 2025-03-27
Dev Status UNMAINTAINED
CI status No Continuous Integration
Released UNRELEASED
Tags No category tags.
Contributing Help Wanted (0)
Good First Issues (0)
Pull Requests to Review (0)

Package Description

Co-LRIO

Additional Links

No additional links.

Maintainers

  • Shipeng Zhong

Authors

  • Shipeng Zhong

CoLRIO

A ROS2 package of CoLRIO: LiDAR-Ranging-Inertial Centralized State Estimation for Robotic Swarms.

https://github.com/PengYu-Team/zhongshp/assets/41199568/81985d82-983c-4eca-898b-43e8f84e7b45

Author

Shipeng Zhong & Dapeng Feng & Zhiqiang Chen

Prerequisites

  • Ubuntu ROS2 Foxy (Robot Operating System 2 on Ubuntu 20.04)
  • CMake (Compilation Configuration Tool)
  • PCL (Default Point Cloud Library on Ubuntu work normally)
  • Eigen (Default Eigen library on Ubuntu work normally)
  • GTSAM 4.2a8 (Georgia Tech Smoothing and Mapping library)

Compilation

Build CoLRIO:

  mkdir -p ~/cslam_ws/src
  cd ~/cslam_ws/src
  git clone https://github.com/zhongshp/Co-LRIO.git
  cd ../
  colcon build --symlink-install
  

Run with Dataset

  • S3E dataset. The datasets are configured to run with default parameter.
  ros2 launch co_lrio run.launch.py
  ros2 bag play *your-bag-path*
  
  • [our dataset] please also found it in S3E dataset.

    Citation

    This work is published in IEEE ICRA 2024 conference, and please cite related papers:

@INPROCEEDINGS{10611672,
  author={Zhong, Shipeng and Chen, Hongbo and Qi, Yuhua and Feng, Dapeng and Chen, Zhiqiang and Wu, Jin and Wen, Weisong and Liu, Ming},
  booktitle={2024 IEEE International Conference on Robotics and Automation (ICRA)}, 
  title={CoLRIO: LiDAR-Ranging-Inertial Centralized State Estimation for Robotic Swarms}, 
  year={2024},
  volume={},
  number={},
  pages={3920-3926},
  keywords={Simultaneous localization and mapping;Accuracy;Scalability;Collaboration;Computational efficiency;Sensors;Servers},
  doi={10.1109/ICRA57147.2024.10611672}}

@ARTICLE{10740801,
  author={Feng, Dapeng and Qi, Yuhua and Zhong, Shipeng and Chen, Zhiqiang and Chen, Qiming and Chen, Hongbo and Wu, Jin and Ma, Jun},
  journal={IEEE Robotics and Automation Letters}, 
  title={S3E: A Multi-Robot Multimodal Dataset for Collaborative SLAM}, 
  year={2024},
  volume={9},
  number={12},
  pages={11401-11408},
  keywords={Simultaneous localization and mapping;Robot sensing systems;Synchronization;Trajectory;Global navigation satellite system;Collaboration;Accuracy;Motion capture;Robot localization;Multi-robot systems;Multi-robot SLAM;data sets for SLAM;SLAM},
  doi={10.1109/LRA.2024.3490402}}

Acknowledgement

The Leaderboard is shown as follow: Leaderboard

And the hardware and results are shown as follow: results table

  • CoLRIO depends on FAST-GICP (Kenji Koide, Masashi Yokozuka, Shuji Oishi, and Atsuhiko Banno, “Voxelized GICP for fast and accurate 3D point cloud registration”.).

  • CoLRIO depends on GncOptimizer (Yang, Antonante, Tzoumas, Carlone, “Graduated Non-Convexity for Robust Spatial Perception: From Non-Minimal Solvers to Global Outlier Rejection”).

CHANGELOG
No CHANGELOG found.

Wiki Tutorials

This package does not provide any links to tutorials in it's rosindex metadata. You can check on the ROS Wiki Tutorials page for the package.

Launch files

No launch files found

Plugins

No plugins found.

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