{"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/visual-slam-based-localization-and-navigation","title":"Visual SLAM-based Localization and Navigation for Service Robots: The Pepper Case","arxiv_id":"1811.08414","date":"2018-11-20","proceeding":null,"authors":["Cristopher Gómez","Matías Mattamala","Tim Resink","Javier Ruiz-del-Solar"],"abstract":"We propose a Visual-SLAM based localization and navigation system for service\nrobots. Our system is built on top of the ORB-SLAM monocular system but\nextended by the inclusion of wheel odometry in the estimation procedures. As a\ncase study, the proposed system is validated using the Pepper robot, whose\nshort-range LIDARs and RGB-D camera do not allow the robot to self-localize in\nlarge environments. The localization system is tested in navigation tasks using\nPepper in two different environments: a medium-size laboratory, and a\nlarge-size hall.","url_abs":"http://arxiv.org/abs/1811.08414v1","url_pdf":"http://arxiv.org/pdf/1811.08414v1.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":"visual-slam-based-localization-and-navigation","repo_url":"https://github.com/parkersell/Robomower","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"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}