{"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/view-planning-and-navigation-algorithms-for","title":"View Planning and Navigation Algorithms for Autonomous Bridge Inspection with UAVs","arxiv_id":"1910.02786","date":"2019-10-03","proceeding":null,"authors":["Kevin Yu","Prajwal Shanthakumar","Jonah Orevillo","Eric Bianchi","Matthew Hebdon","Pratap Tokekar"],"abstract":"We study the problem of infrastructure inspection using an Unmanned Aerial Vehicle (UAV) in box girder bridge environments. We consider a scenario where the UAV needs to fully inspect box girder bridges and localize along the bridge surface when standard methods like GPS and optical flow are denied. Our method for overcoming the difficulties of box girder bridges consist of creating local navigation routines, a supervisor, and a planner. The local navigation routines use two 2D Lidars for girder and column flight. For switching between local navigation routines we implement a supervisor which dictates when the UAV is able to switch between local navigation routines. Lastly, we implement a planner to calculate the path along that box girder bridge that will minimize the flight time of the UAV. With local navigation routines, a supervisor, and a planner we construct a system that can fully and autonomously inspect box girder bridges when standard methods are unavailable.","url_abs":"https://arxiv.org/abs/1910.02786v1","url_pdf":"https://arxiv.org/pdf/1910.02786v1.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":"links_only","authors_date_abstract":"arXiv metadata, CC0 1.0 (https://info.arxiv.org/help/license), from the Kaggle arXiv metadata snapshot of 2026-09-12"},"code_links":[{"paper_slug":"view-planning-and-navigation-algorithms-for","repo_url":"https://github.com/raaslab/WallFollow","is_official":1,"mentioned_in_paper":0,"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}