000171114 001__ 171114
000171114 005__ 20260515150543.0
000171114 0247_ $$2doi$$a10.1109/IROS60139.2025.11247218
000171114 0248_ $$2sideral$$a149219
000171114 037__ $$aART-2025-149219
000171114 041__ $$aeng
000171114 100__ $$aFontan, Alejandro
000171114 245__ $$aVSLAM-LAB: A Comprehensive Framework for Visual SLAM Methods and Datasets
000171114 260__ $$c2025
000171114 5060_ $$aAccess copy available to the general public$$fUnrestricted
000171114 5203_ $$aVisual Simultaneous Localization and Mapping (VSLAM) research faces significant challenges due to fragmented toolchains, complex system configurations, and inconsistent evaluation methodologies. To address these issues, we present VSLAM-LAB, a unified framework designed to streamline the development, evaluation, and deployment of VSLAM systems. VSLAM-LAB simplifies the entire workflow by enabling seamless compilation and configuration of VSLAM algorithms, automated dataset downloading and preprocessing, and standardized experiment design, execution, and evaluation. All of these
features are accessible through a single command-line interface. The framework supports a wide range of VSLAM systems and datasets, offering broad compatibility and extendability while promoting reproducibility through consistent evaluation metrics and analysis tools. By reducing implementation complexity and minimizing configuration overhead, VSLAM-LAB empowers researchers to focus on advancing VSLAM methodologies and accelerates progress toward scalable, real-world solutions. We demonstrate the ease with which user-relevant benchmarks can be created: here, we introduce difficulty-level-based categories, but one could envision environment-specific or condition-specific categories.
000171114 540__ $$9info:eu-repo/semantics/openAccess$$aAll rights reserved$$uhttp://www.europeana.eu/rights/rr-f/
000171114 655_4 $$ainfo:eu-repo/semantics/article$$vinfo:eu-repo/semantics/acceptedVersion
000171114 700__ $$aFischer, Tobias
000171114 700__ $$0(orcid)0000-0003-1368-1151$$aCivera, Javier$$uUniversidad de Zaragoza
000171114 700__ $$aMilford, Michael
000171114 7102_ $$15007$$2520$$aUniversidad de Zaragoza$$bDpto. Informát.Ingenie.Sistms.$$cÁrea Ingen.Sistemas y Automát.
000171114 773__ $$g(2025), [8 pp.]$$pProc. IEEE/RSJ Int. Conf. Intell. Rob. Syst.$$tProceedings of the ... IEEE/RSJ International Conference on Intelligent Robots and Systems$$x2153-0858
000171114 8564_ $$s12568278$$uhttps://zaguan.unizar.es/record/171114/files/texto_completo.pdf$$yPostprint
000171114 8564_ $$s3203721$$uhttps://zaguan.unizar.es/record/171114/files/texto_completo.jpg?subformat=icon$$xicon$$yPostprint
000171114 909CO $$ooai:zaguan.unizar.es:171114$$particulos$$pdriver
000171114 951__ $$a2026-05-15-15:02:32
000171114 980__ $$aARTICLE