A Statistical Analysis of Commercial Articulated Industrial Robots and Cobots

A Statistical Analysis of Commercial Articulated Industrial Robots and Cobots | 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 Statistical Analysis of Commercial Articulated Industrial Robots and Cobots Peyman Amiri, Marcus Müller, Matthew Southgate, Theodoros Theodoridis, and 3 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-3946319/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 This paper undertakes a statistical analysis and review of commercial articulated industrial robots and collaborative robots (cobots) based on their documented specifications such as maximum payload, weight, reach, repeatability, average maximum angular speed and degrees of freedom (DOF). This elucidates the state-of-the-art of these robots, discerns the prevailing priorities and focus of the industry, and identifies both limitations and potential gaps. Industrial robots and cobots are compared and the respective advantages and limitations of industrial cobots are ascertained. Additionally, three novel factors are introduced in this survey as metrics to evaluate the efficiency and performance of industrial robots and cobots. Subsequently, the statistical distributions of these factors are investigated to obtain a systematic method for robot selection. An accompanying program has been developed and uploaded to GitHub which takes the required specifications and returns a list of proper and efficient robots sourced from different companies according to the aforementioned method. Although some robot makers provide some proprietary internal software to assist customers in finding their appropriate robots, the software just considers their own products and does not include those made by other manufacturers. In the end, specifications exhibiting strong correlations are compared in pairs to find out trends and relations between them within each company and across them all. This explains the reason behind these interrelationships, the design purpose of robot makers, and the limitations of industrial robots and cobots. Additionally, this helps industries predict the dependent specifications of articulated robots based on the specifications they require. Statistical Analysis Statistical Review Industrial Robot Cobot Robot efficiency Robot selection 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-3946319","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":273113544,"identity":"0a3b45d8-27db-40a7-8675-b9cae640c6ca","order_by":0,"name":"Peyman 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