paper-with-me

Papers

COSMO-Bench: A Benchmark for Collaborative SLAM Optimization

2025-08-22 · Daniel McGann, Easton R. Potokar, Michael Kaess arxiv

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

📄 PDF Abstract BibTeX arXiv:2508.16731

Code (0)

등록된 구현이 없습니다.

Tasks

Distributed Optimization

Similar Papers 제목 키워드 기반

S3E: A Multi-Robot Multimodal Dataset for Collaborative SLAM

2022-10-25 · Dapeng Feng, Yuhua Qi, Shipeng Zhong, Zhiqiang Chen 외

The burgeoning demand for collaborative robotic systems to execute complex tasks collectively has intensified the research community's focus on advancing simultaneous localization and mapping (SLAM) in a cooperative cont…

DiversitySimultaneous Localization and Mapping

MAGS-SLAM: Monocular Multi-Agent Gaussian Splatting SLAM for Geometrically and Photometrically Consistent Reconstruction

2026-05-11 · Zhihao Cao, Qi Shao, Shuhao Zhai, Jing Zhang 외 arxiv

Collaborative photorealistic 3D reconstruction from multiple agents enables rapid large-scale scene capture for virtual production and cooperative multi-robot exploration. While recent 3D Gaussian Splatting (3DGS) SLAM a…

3D Reconstruction

COVINS: Visual-Inertial SLAM for Centralized Collaboration

2021-08-12 · Patrik Schmuck, Thomas Ziegler, Marco Karrer, Jonathan Perraudin 외

Collaborative SLAM enables a group of agents to simultaneously co-localize and jointly map an environment, thus paving the way to wide-ranging applications of multi-robot perception and multi-user AR experiences by elimi…

global-optimization

CP-SLAM: Collaborative Neural Point-based SLAM System

2023-11-14 · NeurIPS 2023 11

This paper presents a collaborative implicit neural simultaneous localization and mapping (SLAM) system with RGB-D image sequences, which consists of complete front-end and back-end modules including odometry, loop detec…

global-optimizationSimultaneous Localization and Mapping

CoMo3R-SLAM: Collaborative Monocular Dense SLAM with Learned 3D Reconstruction Priors for Outdoor Multi-Agent Systems

2026-05-28 · Zhihao Cao, Qi Shao, Shuhao Zhai, Feng Tian 외 arxiv

Collaborative dense SLAM is essential for multi-robot teams to achieve scalable and consistent 3D perception across large-scale outdoor environments. Existing systems typically depend on depth sensors, incurring signific…

3D Reconstruction