{"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/orb-slam-a-versatile-and-accurate-monocular","title":"ORB-SLAM: a Versatile and Accurate Monocular SLAM System","arxiv_id":"1502.00956","date":"2015-02-03","proceeding":null,"authors":["Raul Mur-Artal","J. M. M. Montiel","Juan D. Tardos"],"abstract":"This paper presents ORB-SLAM, a feature-based monocular SLAM system that\noperates in real time, in small and large, indoor and outdoor environments. The\nsystem is robust to severe motion clutter, allows wide baseline loop closing\nand relocalization, and includes full automatic initialization. Building on\nexcellent algorithms of recent years, we designed from scratch a novel system\nthat uses the same features for all SLAM tasks: tracking, mapping,\nrelocalization, and loop closing. A survival of the fittest strategy that\nselects the points and keyframes of the reconstruction leads to excellent\nrobustness and generates a compact and trackable map that only grows if the\nscene content changes, allowing lifelong operation. We present an exhaustive\nevaluation in 27 sequences from the most popular datasets. ORB-SLAM achieves\nunprecedented performance with respect to other state-of-the-art monocular SLAM\napproaches. For the benefit of the community, we make the source code public.","url_abs":"http://arxiv.org/abs/1502.00956v2","url_pdf":"http://arxiv.org/pdf/1502.00956v2.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":"orb-slam-a-versatile-and-accurate-monocular","repo_url":"https://github.com/lyffly/Python-3DPointCloud-and-RGBD","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"none","reach":{"status":"ok","spdx":"Apache-2.0"}},{"paper_slug":"orb-slam-a-versatile-and-accurate-monocular","repo_url":"https://github.com/raulmur/ORB_SLAM","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":0,"framework":"tf","reach":{"status":"ok","spdx":"NOASSERTION"}}],"tasks":[{"task_slug":"simultaneous-localization-and-mapping","task_name":"Simultaneous Localization and Mapping"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":"https://app.syntology.ai/?focus=1502.00956","mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}