Two Key Algorithms for Intelligent Inspection Robots in Electric Bicycle Charging Sheds

Two Key Algorithms for Intelligent Inspection Robots in Electric Bicycle Charging Sheds | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Article Two Key Algorithms for Intelligent Inspection Robots in Electric Bicycle Charging Sheds YINGJIAN AN, GE WEI This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-5542971/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 05 May, 2025 Read the published version in Scientific Reports → Version 1 posted 7 You are reading this latest preprint version Abstract The deployment of intelligent inspection robots in electric bicycle charging sheds is critical for preventing fire hazards, yet faces challenges in navigating narrow passages and recognizing small components. This paper proposes two enhanced algorithms to address these issues: (1) a multi-root node RRT* (MS-RRT*) for efficient narrow-channel path planning, and (2) an improved SOLOv2-based instance segmentation method for small-target recognition. The MS-RRT* introduces dynamic secondary root nodes with constrained expansion cycles, significantly increasing the probability of traversing narrow channels while reducing sampling nodes in obstacles by 29.36% compared to classical RRT*. For component recognition, the enhanced SOLOv2 algorithm augments feature pyramid outputs with larger hierarchical maps, improving small-target accuracy (e.g., button detection from 52.9–62.5%) without compromising processing speed. Experimental results demonstrate that the proposed MS-RRT* achieves a 100% exploration success rate in narrow channels, outperforming state-of-the-art methods in both efficiency and robustness. The improved SOLOv2 also surpasses Mask R-CNN in multi-category component recognition, ensuring reliable inspection in complex scenarios. These advancements collectively enable 24/7 automated monitoring, addressing critical safety demands in real-world charging infrastructure. Physical sciences/Mathematics and computing/Information technology Physical sciences/Mathematics and computing/Software Intelligent inspection robot RRT* algorithm SOLOv2 algorithm Charging sheds Full Text Additional Declarations No competing interests reported. Cite Share Download PDF Status: Published Journal Publication published 05 May, 2025 Read the published version in Scientific Reports → Version 1 posted Editorial decision: Accepted 23 Apr, 2025 Reviewers agreed at journal 25 Mar, 2025 Reviews received at journal 25 Mar, 2025 Reviewers agreed at journal 24 Mar, 2025 Reviewers invited by journal 24 Mar, 2025 Submission checks completed at journal 22 Mar, 2025 First submitted to journal 22 Mar, 2025 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-5542971","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":433219910,"identity":"d63cdb60-08c2-4423-a9d1-9491d58f2477","order_by":0,"name":"YINGJIAN AN","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA10lEQVRIiWNgGAWjYBACNvb+jw8+VEjY2fc3HyBOCx/PAWPDGWdskg0kjiUQp0VOIsFMmrctjXEDQ44BkQ5jSEiTnMF2mNmc4czHG28Y7OR0GwhqOXDY4gPPYT7L5t7NlnMYko3NDhDSwtjYeHOGxGFmhgNnt0nzMBxI3EZQCzMzgzSPwWHGhgM5z4jUwsbGJM2TAPT+gRw2IrXw8DAbzjhgkyw545ix5RwDIvwiP/8N44OP/yTs+PmbH954U2EnR1ALCpDgITJqkLWQqmMUjIJRMApGBAAAgSRCXHPlMfYAAAAASUVORK5CYII=","orcid":"","institution":"Shanghai Construction Management Vocational Technical College","correspondingAuthor":true,"prefix":"","firstName":"YINGJIAN","middleName":"","lastName":"AN","suffix":""},{"id":433219911,"identity":"4fdba5b8-5420-447c-b476-0de73f8fff43","order_by":1,"name":"GE WEI","email":"","orcid":"","institution":"Shanghai Jiaotong Vocational and Technical College","correspondingAuthor":false,"prefix":"","firstName":"GE","middleName":"","lastName":"WEI","suffix":""}],"badges":[],"createdAt":"2024-11-28 13:38:09","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-5542971/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-5542971/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1038/s41598-025-99825-9","type":"published","date":"2025-05-05T15:57:38+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":82537538,"identity":"4e979842-99d8-47ab-b98f-c9aa13d48210","added_by":"auto","created_at":"2025-05-12 16:08:17","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":499831,"visible":true,"origin":"","legend":"","description":"","filename":"new1.pdf","url":"https://assets-eu.researchsquare.com/files/rs-5542971/v1_covered_1a5c9e30-a3a3-454f-bdad-d761336731b4.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Two Key Algorithms for Intelligent Inspection Robots in Electric Bicycle Charging Sheds","fulltext":[],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":false,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":true,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":true,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"scientific-reports","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"scirep","sideBox":"Learn more about [Scientific Reports](http://www.nature.com/srep/)","snPcode":"","submissionUrl":"","title":"Scientific Reports","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Scientific Reports","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Intelligent inspection robot, RRT* algorithm, SOLOv2 algorithm, Charging sheds","lastPublishedDoi":"10.21203/rs.3.rs-5542971/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-5542971/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eThe deployment of intelligent inspection robots in electric bicycle charging sheds is critical for preventing fire hazards, yet faces challenges in navigating narrow passages and recognizing small components. 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