Author: Yuanyuan Yang, Bowen Xu, Yinjie Li and Sören Schwertfeger

SLAM Hive is a project to enable the systematic, repeatable and reproducable evaluation of SLAM (Simultaneous Localization and Mapping) algorithms. It owns Web graphical user interface, comprehensive evaluation index, user-defined configuration, performance analysis and strong expansibility.

The system is based on Docker container. The use of container technology provides strong expansibility and flexibility for this system. The configuration parameters of mapping tasks and their evaluation results are recorded in the database. Then we can analyze the historical tasks and their corresponding parameter values in detail.

We are working on enable SLAM-Hive to be deployed to clusters to explore the broad parameter space of SLAM algorithms. We will also provide a user management system and more evaluation methods and metrics, as well as other follow-up improvements.

The paper was published at the 2023 IEEE international conference on robotics and automation (ICRA) and is available on arxiv: here

Also 2024 Journal preprint (arXiv PDF): here

The source code is released under GPLv3 license.

We are still working on improving the code reliability. For any technical issues, you can make an issue.

If you use SLAM-Hive in an academic work, please cite:

Yang, Yaxun, Bowen Xu, Yinjie Li, and Sören Schwertfeger, "The SLAM Hive Benchmarking Suite", Robotics and Automation (ICRA), 2023 IEEE International Conference on, 2023.

@inproceedings{
  title={The SLAM Hive Benchmarking Suite},
  author={Yang, Yuanyuan and Xu, Bowen and Li, Yinjie and Schwertfeger, S{\"o}ren},
  booktitle={2023 IEEE international conference on robotics and automation (ICRA)},
  year={2023}
 }

2024 Journal preprint (arXiv PDF):

@misc{liu2024benchmarkingslamalgorithmscloud,
      title={Benchmarking SLAM Algorithms in the Cloud: The SLAM Hive Benchmarking Suite}, 
      author={Xinzhe Liu and Yuanyuan Yang and Bowen Xu and Delin Feng and Sören Schwertfeger},
      year={2024},
      eprint={2406.17586},
      archivePrefix={arXiv},
      primaryClass={cs.RO},
      url={https://arxiv.org/abs/2406.17586}, 
}

The repositories in project are divided into four parts.

The main part of SLAM-Hive is slam_hive_web. You can see the installation help in https://github.com/SLAM-Hive/slam_hive_web/tree/main.

The repository slam_hive_datasets stores scripts for downloading these different datasets.

The repository slam_hive_results stores the evaluation results which we ran and evaluated when testing.

Other repositories like orb-slam2-ros-mono stores the scripts and related files of how to build the algorithm docker image.