COSMO-Bench

Abstract: Recent years have seen a focus on research into distributed optimization algorithms for multi-robot Collaborative Simultaneous Localization and Mapping (C-SLAM). Research in this domain, however, is made difficult by a lack of standard benchmark datasets. Such datasets have been used to great effect in the field of single-robot SLAM, and researchers focused on multi-robot problems would benefit greatly from dedicated benchmark datasets. To address this gap we design and release the Collaborative Open-Source Multi-robot Optimization Benchmark (COSMO-Bench) -- a suite of 24 datasets derived from a state-of-the-art C-SLAM front-end and real-world LiDAR data. For additional details please see our associated publication: https://arxiv.org/abs/2508.16731This entry, hosted through Carnegie Mellon University libraries, serves to host the official dataset release in perpetuity. However, we also support a website that provides a somewhat nicer user interface at cosmobench.comNOTE - Shortly after making this data available we were notified of some issues with the groundtruth of the CU-Multi data on which the `kittredge` and `main_campus` datasets are based. This issue has since been resolved and new versions of the affected datasets have been uploaded. If you are one of the handful of people that downloaded these datasets before September 15th 2025, please update to the corrected versions. To verify that you have the correct versions please see instructions in README.md