English

COSMO-Bench: A Benchmark for Collaborative SLAM Optimization

Robotics 2025-09-16 v2

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 baseline C-SLAM front-end and real-world LiDAR data. Data DOI: https://doi.org/10.1184/R1/29652158

Keywords

Cite

@article{arxiv.2508.16731,
  title  = {COSMO-Bench: A Benchmark for Collaborative SLAM Optimization},
  author = {Daniel McGann and Easton R. Potokar and Michael Kaess},
  journal= {arXiv preprint arXiv:2508.16731},
  year   = {2025}
}
R2 v1 2026-07-01T05:02:22.556Z