Schedules for Pick-and-Place Robots

Schedules for Pick-and-Place Robots | 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PDF Research Article Schedules for Pick-and-Place Robots Peter Buchholz, Alexander Puzicha This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6804075/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 efficiency of pick-and-place robots that put parts into boxes relies on efficient schedules which determine the order in which parts are picked. The scheduling problem can be formulated as an integer linear problem (ILP). However, the resulting ILP cannot be solved for realistic scenarios. Therefor, approximate solution techniques based on local search heuristics and simplified ILPs are introduced. It will be shown that ILP based solutions outperform search heuristics in terms of solution times and solution quality. Finally, we consider an extended version of the pick-and-place robot with two arms. It is shown that the resulting scheduling problem can be handled similarly to the problem for the robot with one arm but the number of variables in the resulting ILP increases from O(P 3 ) for one arm to O(P 6 ) for two arms where P is the number of parts to be picked. Thus, decomposition based approaches are introduced that reduce the scheduling problem for two arms to several problems with one arm. Pick-and-Place Robot ILP Scheduling Traveling Salesman Decomposition Full Text Additional Declarations No competing interests reported. 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-6804075","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":482834355,"identity":"e6702294-699c-4a89-b49b-f3780dc3d19c","order_by":0,"name":"Peter Buchholz","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAABFElEQVRIie2QP0vDQBTAXwkkS9D1gvQ7XAhUAsXP8o6DTtlc6iIHrpGsEb9EXBS3CxlcQl0DCTQh0MmhbhUyNEWhwZzo6HC/4cF7vB/vD4BG83+RAMQGqGF+yOhXFYEou42BgrAgnwr+Xcl+V86tKG2XULHo/jatsXu9ptJ4aK92j+zJwkmxHSt+mBluDhsWVytO0S4Jlealm2PJnsPa8OOxQgtuOgIylpBgRpD0yvpt5oheSQo0z2yFsm6tj6NCV/0Ue6B0qimGOTkqKL8pivP9kHuOoBsvLgKPouTO3eEWsSi9JG9u/FD1sbR5F8tqGsWBW2+7i9OT/mONmJfT5IWnxU6x2CCO6DdW8EOzRqPRaAbsAYyfcXEbvMyzAAAAAElFTkSuQmCC","orcid":"","institution":"TU Dortmund University","correspondingAuthor":true,"prefix":"","firstName":"Peter","middleName":"","lastName":"Buchholz","suffix":""},{"id":482834356,"identity":"fed7948d-5291-475a-97d8-b31be42673a2","order_by":1,"name":"Alexander Puzicha","email":"","orcid":"","institution":"TU Dortmund University","correspondingAuthor":false,"prefix":"","firstName":"Alexander","middleName":"","lastName":"Puzicha","suffix":""}],"badges":[],"createdAt":"2025-06-02 16:38:18","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-6804075/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-6804075/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":86485776,"identity":"bf40dac2-dfec-4f13-8072-f1ad6321ccd8","added_by":"auto","created_at":"2025-07-11 08:20:45","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":420437,"visible":true,"origin":"","legend":"","description":"","filename":"RobotSchedule.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6804075/v1_covered_55a2f86e-41b9-4265-b906-f2abfca99790.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Schedules for Pick-and-Place Robots","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":"Pick-and-Place Robot, ILP, Scheduling, Traveling Salesman, Decomposition","lastPublishedDoi":"10.21203/rs.3.rs-6804075/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6804075/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eThe efficiency of pick-and-place robots that put parts into boxes relies on efficient schedules which determine the order in which parts are picked. 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