Efficient and Lightweight Multi-Constraint Online Planning for Aerial Tracking of Random Targets in Complex Environments

Efficient and Lightweight Multi-Constraint Online Planning for Aerial Tracking of Random Targets in Complex 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 Efficient and Lightweight Multi-Constraint Online Planning for Aerial Tracking of Random Targets in Complex Environments Zhipeng Yang, Feng Yu, Fanzhe Kong, Fuyong Wang This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6277965/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 Tracking randomly moving targets autonomously by quadrotors in complex environments has always been a significant challenge. Most existing research focuses on unobstructed scenarios and fails to provide comprehensive and computationally efficient solutions. In this paper, we present an online trajectory planning framework. By using polynomial trajectory representations, we formulate various constraints to achieve robust tracking of dynamic objects in intricate environmental situations. First, we developed a simple and efficient object detection and motion prediction method. Then, we deeply analyze the analytical requirements for effective tracking. Next, we propose an intuitive augmented-awareness path finding approach. Finally, by considering trajectory smoothness, obstacle avoidance, and dynamic feasibility, we establish a spatio-temporal joint optimization framework that can operate efficiently at the millisecond level. Notably, the obstacle avoidance strategy we adopt is designed to reduce computational cost. Experimental results show that our method can handle more complex scenarios well while maintaining lower computational requirements. Aerial robot Target detection Target tracking Trajectory optimization Autonomous navigation Full Text Additional Declarations No competing interests reported. Supplementary Files Dronetrackingvideo.mp4 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-6277965","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":442276831,"identity":"a17ae421-fd0a-4f9b-9fcf-f36da40b3ea9","order_by":0,"name":"Zhipeng Yang","email":"","orcid":"","institution":"Nankai University","correspondingAuthor":false,"prefix":"","firstName":"Zhipeng","middleName":"","lastName":"Yang","suffix":""},{"id":442276832,"identity":"ae44f4f2-92a3-410f-86cd-602ef598051d","order_by":1,"name":"Feng Yu","email":"","orcid":"","institution":"Nankai University","correspondingAuthor":false,"prefix":"","firstName":"Feng","middleName":"","lastName":"Yu","suffix":""},{"id":442276833,"identity":"cfa9106d-431f-4b59-9f03-cce1ed6b1a39","order_by":2,"name":"Fanzhe Kong","email":"","orcid":"","institution":"Nankai University","correspondingAuthor":false,"prefix":"","firstName":"Fanzhe","middleName":"","lastName":"Kong","suffix":""},{"id":442276834,"identity":"3314e973-6a90-4ecd-afd6-e73e32b8da12","order_by":3,"name":"Fuyong Wang","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA6klEQVRIie3QMQrCMBiG4V+ETIJrHbxDIRAdRK/SIKRLcRGkY0HIqLMIeoV6g5SALlrXiA6dioND3RwErYhrWjfBvEPI8D0EAmAy/Wo+dPITATgAlaAU2QL7nsg3gTLE3uzkOeL7QX3OaZZApxmKappoyXbA2hE/Dq3TWloOMBwK1LJ1hAiP4Cs/0kC5QU4kDUUNWVqyvxA74jFdKnd8c+BRgigPJxEXNFRsnb8iiklPXQiIuE9XirG2Y/fxTCKiJY2phzMx6tKFYvhw87vNyWacakkesiroc399VbVg/5pkcC9emUwm0x/3BBmxVNLXuBCjAAAAAElFTkSuQmCC","orcid":"","institution":"Nankai University","correspondingAuthor":true,"prefix":"","firstName":"Fuyong","middleName":"","lastName":"Wang","suffix":""}],"badges":[],"createdAt":"2025-03-21 13:23:21","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-6277965/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-6277965/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":83414938,"identity":"668bd84f-4f34-4b14-bd0f-5658ce3a0373","added_by":"auto","created_at":"2025-05-25 18:16:26","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":3047459,"visible":true,"origin":"","legend":"","description":"","filename":"LaTeX.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6277965/v1_covered_ddf502f4-446e-4f1c-8cf5-f58d2e19f559.pdf"},{"id":80870677,"identity":"ac6fd0a7-572f-4429-a5d1-28d3c55795d7","added_by":"auto","created_at":"2025-04-18 04:58:32","extension":"mp4","order_by":0,"title":"","display":"","copyAsset":false,"role":"supplement","size":6595334,"visible":true,"origin":"","legend":"","description":"","filename":"Dronetrackingvideo.mp4","url":"https://assets-eu.researchsquare.com/files/rs-6277965/v1/45c5d04fdb36dc0ebea62b6c.mp4"}],"financialInterests":"No competing interests reported.","formattedTitle":"Efficient and Lightweight Multi-Constraint Online Planning for Aerial Tracking of Random Targets in Complex Environments","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":"Aerial robot, Target detection, Target tracking, Trajectory optimization, Autonomous navigation","lastPublishedDoi":"10.21203/rs.3.rs-6277965/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6277965/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"Tracking randomly moving targets autonomously by quadrotors in complex environments has always been a significant challenge. 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