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arXiv · 2508.16731

COSMO-Bench: A Benchmark for Collaborative SLAM Optimization

Daniel McGann·Easton R. Potokar·Michael Kaess
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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

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Daniel McGann, Easton R. Potokar, Michael Kaess. 2025-08-22. COSMO-Bench: A Benchmark for Collaborative SLAM Optimization. https://arxiv.org/abs/2508.16731

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