A Self-Cognitive Grasping Strategy for Edge-Distributed Objects Based on Multi-Stage Perception

A Self-Cognitive Grasping Strategy for Edge-Distributed Objects Based on Multi-Stage Perception | 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 A Self-Cognitive Grasping Strategy for Edge-Distributed Objects Based on Multi-Stage Perception Haodong Luo, Mingshan Xie, Wei Zhang This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-9093937/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 6 You are reading this latest preprint version Abstract Robotic grasping plays a crucial role in both industrial and service environments. A significant challenge arises when objects are positioned near the edges of the field of vision or completely outside of it, leading to incomplete or blurry visual data. This issue severely affects grasp accuracy and limits the operational workspace. To address this, we propose an autonomous cognitive grasping strategy based on multi-stage perception. We introduce a Target Exhaustive Search (TES) algorithm to handle objects located outside the camera's field of view. TES divides the workspace into regions and sequentially searches each one. Additionally, we present a Multi-stage Resampling Edge Compensation algorithm (MREC). This algorithm adjusts the camera position using visual feedback and refines the grasping view through coupled motion planning, ensuring objects remain centered via repeated sampling and motion refinement. To dynamically update quaternion grasp data, we develop a TPPR module, which reconstructs the object’s pose after each image capture. Together, these components enhance grasp accuracy under visual constraints. Experiments show that our method outperforms traditional techniques, particularly when objects are near the visual boundary. We achieve a grasp success rate of 88.1% within 6.08 seconds, significantly extending the robot’s effective operational space. Physical sciences/Engineering Physical sciences/Mathematics and computing Grasping range Motion Planning Robotic grasping Visual Perception Full Text Additional Declarations No competing interests reported. Cite Share Download PDF Status: Under Review Version 1 posted Reviewers agreed at journal 12 Apr, 2026 Reviewers invited by journal 10 Apr, 2026 Editor assigned by journal 08 Apr, 2026 Editor invited by journal 24 Mar, 2026 Submission checks completed at journal 21 Mar, 2026 First submitted to journal 21 Mar, 2026 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. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. 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-9093937","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":623650924,"identity":"c86327d2-e13c-448f-959a-153f1847738a","order_by":0,"name":"Haodong Luo","email":"","orcid":"","institution":"Guizhou University","correspondingAuthor":false,"prefix":"","firstName":"Haodong","middleName":"","lastName":"Luo","suffix":""},{"id":623650925,"identity":"b94e1229-76bb-4cbd-bcfc-1c787abc0d2a","order_by":1,"name":"Mingshan Xie","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAuElEQVRIiWNgGAWjYJCCAwwVEIYECVrOkKqFgbGNFC26/WcMD3ycV2tvcID54G0eBrs8glrMbqQlHJy57TizwQG2ZGsehuRiIrQwHzjMu+0Ym8EBHjNpHoYDiQ0EtZw/2HD475xjPAYH+L8RqeVA8oHDjA01EkBb2IjUAvJLz7EDBpKH2Ywt5xgkE+OwM8YfftTU2fMdb354402FHWEtUHCYgYEZRBsQqR4I6ohXOgpGwSgYBSMPAAA1tz4uzm/GOgAAAABJRU5ErkJggg==","orcid":"","institution":"Guizhou University","correspondingAuthor":true,"prefix":"","firstName":"Mingshan","middleName":"","lastName":"Xie","suffix":""},{"id":623650926,"identity":"266ec811-55da-436d-abbe-706333904dab","order_by":2,"name":"Wei Zhang","email":"","orcid":"","institution":"Guizhou University","correspondingAuthor":false,"prefix":"","firstName":"Wei","middleName":"","lastName":"Zhang","suffix":""}],"badges":[],"createdAt":"2026-03-11 12:29:07","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-9093937/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-9093937/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":107484277,"identity":"97cd1b52-2bbf-4887-80e6-9b737e3b81d4","added_by":"auto","created_at":"2026-04-22 02:31:19","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1171315,"visible":true,"origin":"","legend":"","description":"","filename":"file.pdf","url":"https://assets-eu.researchsquare.com/files/rs-9093937/v1_covered_cafca690-8ad0-4e7d-a24b-faf2d2137dac.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"A Self-Cognitive Grasping Strategy for Edge-Distributed Objects Based on Multi-Stage Perception","fulltext":[],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":false,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":false,"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":"Grasping range, Motion Planning, Robotic grasping, Visual Perception","lastPublishedDoi":"10.21203/rs.3.rs-9093937/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-9093937/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eRobotic grasping plays a crucial role in both industrial and service environments. 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