{"id":27435934,"url":"https://github.com/zhongshp/Co-LRIO","last_synced_at":"2025-04-14T19:03:25.341Z","repository":{"id":196420155,"uuid":"692320301","full_name":"zhongshp/Co-LRIO","owner":"zhongshp","description":"A ROS2 package of CoLRIO: LiDAR-Ranging-Inertial Centralized State Estimation for Robotic Swarms.","archived":false,"fork":false,"pushed_at":"2025-03-27T05:07:22.000Z","size":361,"stargazers_count":91,"open_issues_count":6,"forks_count":9,"subscribers_count":2,"default_branch":"master","last_synced_at":"2025-03-27T05:28:19.159Z","etag":null,"topics":["centralized","collaborative-slam","lidar-ranging-inertial"],"latest_commit_sha":null,"homepage":"","language":"C++","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":"apache-2.0","status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/zhongshp.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":null,"license":"LICENSE","code_of_conduct":null,"threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null,"governance":null,"roadmap":null,"authors":null,"dei":null,"publiccode":null,"codemeta":null}},"created_at":"2023-09-16T05:47:49.000Z","updated_at":"2025-03-27T05:07:25.000Z","dependencies_parsed_at":"2024-02-23T08:25:58.869Z","dependency_job_id":"abc0f0ca-6064-4b1b-b620-b97100109812","html_url":"https://github.com/zhongshp/Co-LRIO","commit_stats":null,"previous_names":["pengyu-team/co-lrio"],"tags_count":0,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/zhongshp%2FCo-LRIO","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/zhongshp%2FCo-LRIO/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/zhongshp%2FCo-LRIO/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/zhongshp%2FCo-LRIO/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/zhongshp","download_url":"https://codeload.github.com/zhongshp/Co-LRIO/tar.gz/refs/heads/master","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":248943435,"owners_count":21186958,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2022-07-04T15:15:14.044Z","host_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub","repositories_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories","repository_names_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repository_names","owners_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners"}},"keywords":["centralized","collaborative-slam","lidar-ranging-inertial"],"created_at":"2025-04-14T19:02:26.378Z","updated_at":"2025-04-14T19:03:25.318Z","avatar_url":"https://github.com/zhongshp.png","language":"C++","funding_links":[],"categories":["C++"],"sub_categories":[],"readme":"# CoLRIO\n\nA ROS2 package of CoLRIO: LiDAR-Ranging-Inertial Centralized State Estimation for Robotic Swarms. \n\nhttps://github.com/PengYu-Team/zhongshp/assets/41199568/81985d82-983c-4eca-898b-43e8f84e7b45\n\n## Author\n[Shipeng Zhong](https://github.com/zhongshp) \u0026 [Dapeng Feng](https://github.com/DapengFeng) \u0026 [Zhiqiang Chen](https://github.com/thisparticle)\n\n## Prerequisites\n  - [Ubuntu ROS2 Foxy](http://wiki.ros.org/ROS/Installation) (Robot Operating System 2 on Ubuntu 20.04)\n  - CMake (Compilation Configuration Tool)\n  - [PCL](https://pointclouds.org/downloads/linux.html) (Default Point Cloud Library on Ubuntu work normally)\n  - [Eigen](http://eigen.tuxfamily.org/index.php?title=Main_Page) (Default Eigen library on Ubuntu work normally)\n  - [GTSAM 4.2a8](https://github.com/borglab/gtsam/releases) (Georgia Tech Smoothing and Mapping library)\n\n## Compilation\n  Build CoLRIO:\n  ```\n  mkdir -p ~/cslam_ws/src\n  cd ~/cslam_ws/src\n  git clone https://github.com/zhongshp/Co-LRIO.git\n  cd ../\n  colcon build --symlink-install\n  ```\n## Run with Dataset\n  - [S3E dataset](https://github.com/DapengFeng/S3E). The datasets are configured to run with default parameter.\n  ```\n  ros2 launch co_lrio run.launch.py\n  ros2 bag play *your-bag-path*\n  ```\n  - [our dataset] please also found it in [S3E dataset](https://github.com/DapengFeng/S3E).\n## Citation\nThis work is published in IEEE ICRA 2024 conference, and please cite related papers:\n\n```\n@INPROCEEDINGS{10611672,\n  author={Zhong, Shipeng and Chen, Hongbo and Qi, Yuhua and Feng, Dapeng and Chen, Zhiqiang and Wu, Jin and Wen, Weisong and Liu, Ming},\n  booktitle={2024 IEEE International Conference on Robotics and Automation (ICRA)}, \n  title={CoLRIO: LiDAR-Ranging-Inertial Centralized State Estimation for Robotic Swarms}, \n  year={2024},\n  volume={},\n  number={},\n  pages={3920-3926},\n  keywords={Simultaneous localization and mapping;Accuracy;Scalability;Collaboration;Computational efficiency;Sensors;Servers},\n  doi={10.1109/ICRA57147.2024.10611672}}\n```\n\n```\n@ARTICLE{10740801,\n  author={Feng, Dapeng and Qi, Yuhua and Zhong, Shipeng and Chen, Zhiqiang and Chen, Qiming and Chen, Hongbo and Wu, Jin and Ma, Jun},\n  journal={IEEE Robotics and Automation Letters}, \n  title={S3E: A Multi-Robot Multimodal Dataset for Collaborative SLAM}, \n  year={2024},\n  volume={9},\n  number={12},\n  pages={11401-11408},\n  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},\n  doi={10.1109/LRA.2024.3490402}}\n```\n\n## Acknowledgement\n  - We combined the front end of CoLRIO and the [DLO](https://github.com/vectr-ucla/direct_lidar_odometry) to achieve the 5th position in the [ICCV 2023 LiDAR-Inertial SLAM Challenge](https://superodometry.com/iccv23_challenge_LiI).\n\n  The Leaderboard is shown as follow:\n  ![Leaderboard](https://github.com/PengYu-Team/Co-LRIO/assets/41199568/72168f1d-9c74-43d1-90ce-12383131f464)\n\n  And the hardware and results are shown as follow:\n  ![results table](https://github.com/PengYu-Team/Co-LRIO/assets/41199568/f75e8660-acd9-4961-8964-2e3edba1e965)\n    \n  - CoLRIO depends on [FAST-GICP](https://github.com/SMRT-AIST/fast_gicp) (Kenji Koide, Masashi Yokozuka, Shuji Oishi, and Atsuhiko Banno, \"Voxelized GICP for fast and accurate 3D point cloud registration\".).\n\n  - CoLRIO depends on [GncOptimizer](https://github.com/borglab/gtsam/blob/3a1fe574683f608759eaff4636ab53def600ce84/gtsam/nonlinear/GncOptimizer.h#L45) (Yang, Antonante, Tzoumas, Carlone, \"Graduated Non-Convexity for Robust Spatial Perception: From Non-Minimal Solvers to Global Outlier Rejection\").\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fzhongshp%2FCo-LRIO","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fzhongshp%2FCo-LRIO","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fzhongshp%2FCo-LRIO/lists"}