Design and Field Evaluation of a Solar-Powered CNC-Based Autonomous Seedling Transplanting Robot for Precision Agriculture

Design and Field Evaluation of a Solar-Powered CNC-Based Autonomous Seedling Transplanting Robot for Precision Agriculture | 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 Design and Field Evaluation of a Solar-Powered CNC-Based Autonomous Seedling Transplanting Robot for Precision Agriculture Ghada A. Elgamal, Omar A. Hashem, Nerveen Ehab, A. M. Bassiuny This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8649151/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 Seedling transplantation has a significant impact on crop uniformity, productivity, and resource efficiency. However, conventional manual and electrically driven transplanting systems remain labor-intensive, energy-dependent, and prone to inconsistent planting accuracy under variable field conditions. This paper presents the design and field validation of a solar-powered CNC-based autonomous seedling robot (ASR) for precision agriculture. The proposed system integrates a three-axis CNC mechanism for accurate seedling placement, IoT-enabled monitoring for real-time operation, and sensor-based autonomous navigation to optimize field coverage. A photovoltaic power system enables fully off-grid operation, enhancing sustainability and reducing operational costs. Field experiments conducted on various soil types demonstrate that the ASR reduces planting time by approximately 40% compared to manual transplanting while achieving a 95% planting accuracy. The solar-powered architecture enables continuous operation without external energy sources, resulting in zero operational energy cost during field trials. The results confirm that the ASR effectively addresses key limitations of existing automated transplanting systems, particularly energy dependency and limited adaptability. Beyond technical performance, the proposed system supports sustainable agricultural development by utilizing renewable solar energy, reducing labor dependency, and minimizing environmental impact, offering a scalable solution for next-generation precision agriculture. Autonomous seedling transplanting CNC-based robotics Solar-powered agricultural systems IoT precision agriculture Field robotic automation 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-8649151","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":581324449,"identity":"1ebc6652-6d8a-41db-9937-af6bf404de42","order_by":0,"name":"Ghada A. 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However, conventional manual and electrically driven transplanting systems remain labor-intensive, energy-dependent, and prone to inconsistent planting accuracy under variable field conditions. This paper presents the design and field validation of a solar-powered CNC-based autonomous seedling robot (ASR) for precision agriculture.\u003c/p\u003e \u003cp\u003eThe proposed system integrates a three-axis CNC mechanism for accurate seedling placement, IoT-enabled monitoring for real-time operation, and sensor-based autonomous navigation to optimize field coverage. A photovoltaic power system enables fully off-grid operation, enhancing sustainability and reducing operational costs.\u003c/p\u003e \u003cp\u003eField experiments conducted on various soil types demonstrate that the ASR reduces planting time by approximately 40% compared to manual transplanting while achieving a 95% planting accuracy. The solar-powered architecture enables continuous operation without external energy sources, resulting in zero operational energy cost during field trials.\u003c/p\u003e \u003cp\u003eThe results confirm that the ASR effectively addresses key limitations of existing automated transplanting systems, particularly energy dependency and limited adaptability. 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