A Multi-Objective Framework for Human–Robot Collaborative Assembly with Augmented Reality Visualization

A Multi-Objective Framework for Human–Robot Collaborative Assembly with Augmented Reality Visualization | 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 Research Article A Multi-Objective Framework for Human–Robot Collaborative Assembly with Augmented Reality Visualization Anil Kumar Inkulu, Chiranjibi Champatiray, Eswaran Moorthy, Satish Pujari, and 1 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7054537/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract The increasing complexity of customized manufacturing in Industry 5.0 has amplified the need for human-robot collaboration (HRC) to enhance assembly systems’ flexibility, adaptability, and real-time responsiveness. This study proposes an integrated optimization framework comprising four key modules: Optimal Assembly Sequence Planning (OASP), Optimal Resource Allocation (ORA), Optimal Layout Planning (OLP), and immersive lay out validation using augmented reality (AR). Assembly sequences are developed via a part concatenation strategy, while resource-task assignments are formulated as a multi-criteria optimization problem and solved using the Nelder–Mead simplex algorithm. Layout plan ning employs linear programming under separation constraints to prevent spatial overlap. AR-based visualization enables real-time layout validation and operator interactions. The framework wastested on two industrial case studies—a vibration generator and a transmis sion assembly—demonstrating over 70% reduction in layout generation time compared with modified particle swarm optimization (MPSO) and improvements in space utilization and task sequencing. These results establish the framework as a scalable, digital twin-ready decision support tool for designing adaptive HRC systems in smart manufacturing. Industry 5.0 Reconfigurable HRC Multi-Criteria Optimization Layout Planning Digital twin-ready system Full Text Cite Share Download PDF Status: Posted Version 1 posted 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-7054537","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":510833405,"identity":"091fcdd9-398a-4a69-bacc-83cb3308b973","order_by":0,"name":"Anil Kumar Inkulu","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA30lEQVRIiWNgGAWjYFACxsYDIIqN4TCIlpAhRksDWAsf47EEkBYeouwBa5FjPmMAoglr4Z/d3HCAMcdGno3tzOdXN2oseBjYDx/dgE+LxJ2DQC3b0gzbeM5us845BnQYT1raDbzW3EgEaTmcwCZxdptxDhtQiwSPGV4t8hAt/xPY5N88M875R4QWA4iWAwlsDGeYH+e2EaHFEKQlcVuyYRvDMTPm3D4JHjZCfpG7kf7wwcdtdvLyDYcff875VifHz374GH7vg0AChGKTAJMElSMB5g+kqB4Fo2AUjIKRAwDCgEvaARdu0QAAAABJRU5ErkJggg==","orcid":"https://orcid.org/0000-0001-8926-3832","institution":"Lendi Institute of Engineering and Technology","correspondingAuthor":true,"prefix":"","firstName":"Anil","middleName":"Kumar","lastName":"Inkulu","suffix":""},{"id":510833406,"identity":"6d9dad5d-9f0f-4f2c-a44b-85caef1a62a2","order_by":1,"name":"Chiranjibi Champatiray","email":"","orcid":"","institution":"","correspondingAuthor":false,"prefix":"","firstName":"Chiranjibi","middleName":"","lastName":"Champatiray","suffix":""},{"id":510833407,"identity":"3c063eed-8355-43c0-b7bb-f70a11aa2536","order_by":2,"name":"Eswaran Moorthy","email":"","orcid":"","institution":"","correspondingAuthor":false,"prefix":"","firstName":"Eswaran","middleName":"","lastName":"Moorthy","suffix":""},{"id":510833408,"identity":"77c00162-56f3-4732-9da9-72edaa9543c3","order_by":3,"name":"Satish Pujari","email":"","orcid":"","institution":"","correspondingAuthor":false,"prefix":"","firstName":"Satish","middleName":"","lastName":"Pujari","suffix":""},{"id":510833409,"identity":"b357b842-8734-4f23-9335-c17583514f61","order_by":4,"name":"Raju Bahubalendruni","email":"","orcid":"","institution":"","correspondingAuthor":false,"prefix":"","firstName":"Raju","middleName":"","lastName":"Bahubalendruni","suffix":""}],"badges":[],"createdAt":"2025-07-05 18:16:47","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-7054537/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-7054537/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":101205703,"identity":"6c82b3e1-dcbd-48d7-886e-93a72211f55c","added_by":"auto","created_at":"2026-01-27 09:50:10","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1054725,"visible":true,"origin":"","legend":"","description":"","filename":"Manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7054537/v1_covered_46998a57-839c-4f95-a91a-dcd9e33d631a.pdf"}],"financialInterests":"","formattedTitle":"A Multi-Objective Framework for Human–Robot Collaborative Assembly with Augmented Reality Visualization","fulltext":[],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":false,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"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":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Industry 5.0, Reconfigurable, HRC, Multi-Criteria Optimization, Layout Planning, Digital twin-ready system","lastPublishedDoi":"10.21203/rs.3.rs-7054537/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7054537/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"The increasing complexity of customized manufacturing in Industry 5.0 has amplified the need for human-robot collaboration (HRC) to enhance assembly systems’ flexibility, adaptability, and real-time responsiveness. 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