Time-Optimal Trajectory Planning of Manipulator Based on Terminal Crossover and Steering-based PSO with Disturbance

Time-Optimal Trajectory Planning of Manipulator Based on Terminal Crossover and Steering-based PSO with Disturbance | 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 Time-Optimal Trajectory Planning of Manipulator Based on Terminal Crossover and Steering-based PSO with Disturbance Lei Li, JiaWei Xu, Jianhua Wang This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4156332/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 4 You are reading this latest preprint version Abstract In the contemporary shipbuilding industry, the utilization of manipulator operations has progressively supplanted traditional manual labor. In pursuit of enhancing both efficiency and stability of manipulator operations, this study proposes a trajectory planning methodology. Specifically, a 5-7-5 polynomial interpolation function is devised to accurately map trajectories within the joint space of the manipulator. Subsequently, a constrained optimization model is formulated, aiming to optimize the movement time of the manipulator. To address the optimization challenge, the constrained problem is reformulated into an unconstrained one leveraging the augmented Lagrange multiplier method. To circumvent the risk of local optima, the Terminal Crossover and Steering-based PSO with disturbance (TCSPSO) is adopted for problem-solving. Subsequently, comprehensive simulation experiments are conducted in MATLAB to ascertain the optimal motion time and achieve a smooth motion trajectory for the manipulator. The findings underscore the efficacy of the proposed methodology in significantly reducing the movement time of manipulators while concurrently ensuring their operational stability. manipulator trajectory planning PSO algorithm polynomial interpolation Full Text Cite Share Download PDF Status: Under Review Version 1 posted Reviewers agreed at journal 16 Jul, 2024 Reviewers invited by journal 28 Apr, 2024 Editor assigned by journal 29 Mar, 2024 First submitted to journal 23 Mar, 2024 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-4156332","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":296405608,"identity":"8643bfb9-70d8-4a26-94db-addc0092f6db","order_by":0,"name":"Lei Li","email":"","orcid":"","institution":"Jiangsu University of Science and Technology: Jiangsu University","correspondingAuthor":false,"prefix":"","firstName":"Lei","middleName":"","lastName":"Li","suffix":""},{"id":296405609,"identity":"a23a5dbf-7601-43c7-91f7-a229c0383c2e","order_by":1,"name":"JiaWei Xu","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAx0lEQVRIiWNgGAWjYBACfv7G9g8fKmzsGNsbiNQiOePwMcYZZ9KSmXsOEKnFoCEtjZm35TBj+4wEYrUwnDF7wNsA1Dbz8cYbDDU20QS1mDP3mBtI7rDhk5ydVmzBcCwtt4GQFsuGMwYShmfSmA1n55hJMDYcJqzF4ECOgURi22HG/TfPEK0lLU3iIFBL4wweIrUAA/mwYQMwkBl7gH5JIMYvwKhsfPwHHJWHN974UGNDWAuKIyUSSFEO0UKqjlEwCkbBKBgZAACQ0EXbP0E3/wAAAABJRU5ErkJggg==","orcid":"https://orcid.org/0009-0005-9033-7778","institution":"Jiangsu University of Science and Technology: Jiangsu University","correspondingAuthor":true,"prefix":"","firstName":"JiaWei","middleName":"","lastName":"Xu","suffix":""},{"id":296405610,"identity":"a6104f3c-fa7a-4353-a9d6-41bb03f7f74b","order_by":2,"name":"Jianhua Wang","email":"","orcid":"","institution":"Jiangsu University of Science and Technology: Jiangsu University","correspondingAuthor":false,"prefix":"","firstName":"Jianhua","middleName":"","lastName":"Wang","suffix":""}],"badges":[],"createdAt":"2024-03-24 03:16:38","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-4156332/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4156332/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":55780757,"identity":"14171ef0-28f5-48bb-bd52-61aeb5a5b64d","added_by":"auto","created_at":"2024-05-03 04:43:45","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":3026468,"visible":true,"origin":"","legend":"","description":"","filename":"TimeOptimalTrajectoryPlanning.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4156332/v1_covered_55be49b0-b559-4624-9828-7657ca6e51b8.pdf"}],"financialInterests":"","formattedTitle":"Time-Optimal Trajectory Planning of Manipulator Based on Terminal Crossover and Steering-based PSO with Disturbance","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":"journal-of-the-brazilian-society-of-mechanical-sciences-and-engineering","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"bmse","sideBox":"Learn more about [Journal of the Brazilian Society of Mechanical Sciences and Engineering](http://link.springer.com/journal/40430)","snPcode":"40430","submissionUrl":"https://www.editorialmanager.com/bmse/default2.aspx","title":"Journal of the Brazilian Society of Mechanical Sciences and Engineering","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"manipulator, trajectory planning, PSO algorithm, polynomial interpolation","lastPublishedDoi":"10.21203/rs.3.rs-4156332/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4156332/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eIn the contemporary shipbuilding industry, the utilization of manipulator operations has progressively supplanted traditional manual labor. 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