Automatic placement of cameras in a particle accelerator using a 3D engine and computational optimization

Automatic placement of cameras in a particle accelerator using a 3D engine and computational optimization | 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 Automatic placement of cameras in a particle accelerator using a 3D engine and computational optimization N.C. Cruz, M. Rouret, E.M. Ortigosa, E. Ros, J.A. Garrido This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-3903339/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 Particle accelerators have high-radiation parts requiring remote maintenance tasks, which involve using cameras generally placed by human experts. This work addresses camera placement through black-box global optimization. This approach allows opting for automated solutions and relieving experts of that responsibility. The formulation of the objective function hides the environment-specific placement constraints and shows domain ones only. The proposed methodology allows the use of regular meta-heuristics for standard black-box box-constrained problems, as it is only necessary to honor the bounds of variables. Accordingly, the optimization algorithm used is the genetic algorithm provided by the Global Optimization Toolbox of MATLAB. The objective function computation relies on the simulation capabilities of the widespread Unity game engine. It brings us an integrated framework for defining the target process to consider and for checking the different proposals visually. Based on this framework, this work reconstructs the virtual reality simulation of a maintenance task in a particle accelerator. The results obtained show that the camera positioning achieved by the proposal for four cameras and one target process outperforms the arrangement defined by a human expert. Simulation-based optimization Camera placement Particle accelerator Black-box global optimization Constraint relaxation Genetic algorithm 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-3903339","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":269951250,"identity":"1b2ae4b3-684a-43ad-8889-cdccee50845c","order_by":0,"name":"N.C. Cruz","email":"","orcid":"","institution":"University of Granada","correspondingAuthor":false,"prefix":"","firstName":"N.C.","middleName":"","lastName":"Cruz","suffix":""},{"id":269951251,"identity":"9b45a05d-e944-44bb-b043-64bb730ae5ca","order_by":1,"name":"M. 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