Robust 3D Localization for UAV Navigation Using Event Cameras and IMU for Indoor Environments

Robust 3D Localization for UAV Navigation Using Event Cameras and IMU for Indoor Environments | 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 Robust 3D Localization for UAV Navigation Using Event Cameras and IMU for Indoor Environments David Tejero-Ruiz, David Solís-Martín, Francisco J. Pérez-Grau, and 1 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-5012474/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 For proper navigation of Unmanned Aerial Vehicles (UAVs), it is necessary to know their position in real-time to ensure safe navigation. Determining position in outdoor spaces is quite well solved. On the other hand, in indoor spaces, existing solutions are either imprecise or excessively costly. In this paper, the 3D localization problem is addressed in the context of UAV navigation. The main purpose of this work is to develop and evaluate a robust real-time localization scheme using exclusively the information from an embedded Event Camera and an IMU (Inertial Measurement Unit). Deep learning techniques and robust computer vision algorithms are implemented together to accurately compute the UAV pose, leveraging the strengths of well-established visual-inertial odometry algorithms and the intrinsic advantages of Event Cameras, such as high dynamic range and absence of motion blur. Throughout this study, state-of-the-art techniques are selected, refined, implemented, and evaluated. The proposed system demonstrated good performance and acceptable precision specially in situation with abrupt lighting changes. Event camera Unmanned Aerial Vehicle Deep Learning Visual-Inertial Odometry Sensor Fusion Pose Estimation 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. 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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-5012474","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":360626295,"identity":"17c3a08e-1528-417f-b531-2e69d70f3aff","order_by":0,"name":"David Tejero-Ruiz","email":"","orcid":"","institution":"Seville University","correspondingAuthor":false,"prefix":"","firstName":"David","middleName":"","lastName":"Tejero-Ruiz","suffix":""},{"id":360626296,"identity":"7644cd2e-1a1b-4d12-a076-41bfab0ab48b","order_by":1,"name":"David Solís-Martín","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAnUlEQVRIiWNgGAWjYDCCAwyMBxIYbEjTwgDUkkaqFgaGwyTo4Dt/+MCBB3/OJ85vYD78gSgtkjfSEg4ktt1O3HCALU2CKC0GN3gMDiQ2ALUw8JgR5zCD82cMDiT8OQd0GP9n4hxmcCAHqIUNaNEBHgbiHAb1S7LxhsNsZsRpAYbYwYc//tjJzm9vfkycwxCAmUT1o2AUjIJRMArwAADMgDeiiLLKuwAAAABJRU5ErkJggg==","orcid":"","institution":"Seville University","correspondingAuthor":true,"prefix":"","firstName":"David","middleName":"","lastName":"Solís-Martín","suffix":""},{"id":360626297,"identity":"c678e8a6-522d-46bb-9aee-ef363be346eb","order_by":2,"name":"Francisco J. 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