{"about":{"site":"https://codewithpapers.app","non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page"},"url":"/paper/long-term-large-scale-mapping-and","title":"Long-term Large-scale Mapping and Localization Using maplab","arxiv_id":"1805.10994","date":"2018-05-28","proceeding":null,"authors":["Marcin Dymczyk","Marius Fehr","Thomas Schneider","Roland Siegwart"],"abstract":"This paper discusses a large-scale and long-term mapping and localization\nscenario using the maplab open-source framework. We present a brief overview of\nthe specific algorithms in the system that enable building a consistent map\nfrom multiple sessions. We then demonstrate that such a map can be reused even\na few months later for efficient 6-DoF localization and also new trajectories\ncan be registered within the existing 3D model. The datasets presented in this\npaper are made publicly available.","url_abs":"http://arxiv.org/abs/1805.10994v1","url_pdf":"http://arxiv.org/pdf/1805.10994v1.pdf","source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","row_kind":"abstracts"},"code_links":[{"paper_slug":"long-term-large-scale-mapping-and","repo_url":"https://github.com/ethz-asl/maplab","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":0,"framework":"none","reach":null}],"tasks":[],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}