arXiv:2508.16731 · v3
COSMO-Bench: A Benchmark for Collaborative SLAM Optimization
摘要
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
作者备注：This article has been accepted for publication in IEEE International Conference on Robotics and Automation. DOI: 10.1109/ICRA57385.2026.11696499