ICRA 2026poster0 citations

COSMO-Bench: A Benchmark for Collaborative SLAM Optimization

Daniel McGann, Easton Potokar, Michael Kaess

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.

Multi-Robot SLAMSLAMMulti-Robot Systems
COSMO-Bench: A Benchmark for Collaborative SLAM Optimization · ICRA 2026