{"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/skimap-an-efficient-mapping-framework-for","title":"SkiMap: An Efficient Mapping Framework for Robot Navigation","arxiv_id":"1704.05832","date":"2017-04-19","proceeding":null,"authors":["Daniele De Gregorio","Luigi Di Stefano"],"abstract":"We present a novel mapping framework for robot navigation which features a\nmulti-level querying system capable to obtain rapidly representations as\ndiverse as a 3D voxel grid, a 2.5D height map and a 2D occupancy grid. These\nare inherently embedded into a memory and time efficient core data structure\norganized as a Tree of SkipLists. Compared to the well-known Octree\nrepresentation, our approach exhibits a better time efficiency, thanks to its\nsimple and highly parallelizable computational structure, and a similar memory\nfootprint when mapping large workspaces. Peculiarly within the realm of mapping\nfor robot navigation, our framework supports realtime erosion and\nre-integration of measurements upon reception of optimized poses from the\nsensor tracker, so as to improve continuously the accuracy of the map.","url_abs":"http://arxiv.org/abs/1704.05832v1","url_pdf":"http://arxiv.org/pdf/1704.05832v1.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":"skimap-an-efficient-mapping-framework-for","repo_url":"https://github.com/m4nh/skimap_ros","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":1,"framework":"tf","reach":null}],"tasks":[{"task_slug":"robot-navigation","task_name":"Robot Navigation"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}