Reactive Local Navigation for Autonomous Exploration Using Riemannian Motion Policies and Hierarchical Wavemaps

Reactive Local Navigation for Autonomous Exploration Using Riemannian Motion Policies and Hierarchical Wavemaps | 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 Article Reactive Local Navigation for Autonomous Exploration Using Riemannian Motion Policies and Hierarchical Wavemaps Marwan Zaghloul, Mohammed Ibrahim Awad, Omar Shehata, Diaa Emad This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-9564893/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 5 You are reading this latest preprint version Abstract Autonomous exploration requires local navigation that reacts to newly observed geometry under strict runtime constraints while respecting non-holonomic motion. This paper investigates whether waypoint execution must rely on finite-horizon local optimization or can instead use reactive geometric control with hierarchical perception.We present RMP-Nav , a reactive local planner for differential-drive robots that composes Riemannian Motion Policies for goal attraction, yaw regulation, and obstacle avoidance on a robot-centric hierarchical wavemap. A key contribution is a virtual lookahead--pullback mechanism that converts obstacle-induced lateral repulsion into steering commands, enabling non-holonomic waypoint execution without trajectory sampling.The method is evaluated in simulation within the Autonomous Exploration Development Environment as a drop-in replacement for the optimization-based FALCO planner across Campus, Forest, and Garage scenarios under identical sensing, mapping, and planning pipelines. In these environments, RMP-Nav reduces mean local-planning runtime from the millisecond range to below 0.1 ms per invocation while achieving waypoint-completion scores comparable to FALCO in Campus and Forest, with a moderate decrease in Garage. Across trials, RMP-Nav also exhibits lower jerk, increased obstacle clearance, and greater distance traveled per CPU-second.These results indicate that reactive RMP-based control with hierarchical volumetric perception is effective in geometry-dominated environments, while finite-horizon optimization remains advantageous in topologically constrained settings. Physical sciences/Engineering Physical sciences/Mathematics and computing Physical sciences/Physics Autonomous Exploration Local navigation Riemannian Motion Policies Wavemap Volumetric mapping Mobile robots Full Text Additional Declarations No competing interests reported. Cite Share Download PDF Status: Under Review Version 1 posted Reviewers invited by journal 08 May, 2026 Editor invited by journal 07 May, 2026 Editor assigned by journal 30 Apr, 2026 Submission checks completed at journal 30 Apr, 2026 First submitted to journal 29 Apr, 2026 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-9564893","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":637136943,"identity":"1c3d7c71-8865-4aa6-ac25-28246bc4ebe2","order_by":0,"name":"Marwan Zaghloul","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAABCUlEQVRIie3OsUrDQBzH8TsC1+XSrBExvsJfBBeHvMpJobek0DFjinBdUl1b8CH0Df7hwOkGx2w2i1MHwSVIRC9blisZhd53OC6BD/cjxOf7h0WTVaG7nCWDf+I4OSt1hdxMr8cTqOczDFVyV4wmBDPA2NzIx/P1G2k7badmQD6/3YIWBhDy+WL3ZJZ0o7SdegC6e3CTgJaAwrwunutMkLDQdmoGQVi6CQs4YKV+ZWoJ7eywtCc/RwhnTFQrxQTEEgPO7CuxJaR1k5gHqIlhV9s6I/pCSR6bj2W1KdwkfW/uv0jOLqOtbJpDd5tE69nLvu3cZLgRsD/7K1I1ikz2g49xr/h8Pt9p9AfI31ru6GIJPgAAAABJRU5ErkJggg==","orcid":"","institution":"Ain Shams University","correspondingAuthor":true,"prefix":"","firstName":"Marwan","middleName":"","lastName":"Zaghloul","suffix":""},{"id":637136944,"identity":"cfa3addf-5f62-46a8-8c10-c26e13759a2e","order_by":1,"name":"Mohammed Ibrahim Awad","email":"","orcid":"","institution":"Ain Shams University","correspondingAuthor":false,"prefix":"","firstName":"Mohammed","middleName":"Ibrahim","lastName":"Awad","suffix":""},{"id":637136945,"identity":"7cd5fdc5-7a13-40c9-be03-4ab6ffa3cae9","order_by":2,"name":"Omar Shehata","email":"","orcid":"","institution":"Ain Shams University","correspondingAuthor":false,"prefix":"","firstName":"Omar","middleName":"","lastName":"Shehata","suffix":""},{"id":637136946,"identity":"37bf2d0c-8532-4802-9d60-338067710081","order_by":3,"name":"Diaa Emad","email":"","orcid":"","institution":"Ain Shams University","correspondingAuthor":false,"prefix":"","firstName":"Diaa","middleName":"","lastName":"Emad","suffix":""}],"badges":[],"createdAt":"2026-04-29 11:08:43","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-9564893/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-9564893/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":109759396,"identity":"815aaac4-0200-4538-9e74-093cf010c819","added_by":"auto","created_at":"2026-05-22 07:26:55","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":4396581,"visible":true,"origin":"","legend":"","description":"","filename":"ZaghloulRMPNavSource.pdf","url":"https://assets-eu.researchsquare.com/files/rs-9564893/v1_covered_06d77805-e63b-49c3-b8a7-90d68130ea26.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Reactive Local Navigation for Autonomous Exploration Using Riemannian Motion Policies and Hierarchical\nWavemaps","fulltext":[],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":false,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"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":"scientific-reports","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"scirep","sideBox":"Learn more about [Scientific Reports](http://www.nature.com/srep/)","snPcode":"","submissionUrl":"","title":"Scientific Reports","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Scientific Reports","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Autonomous Exploration, Local navigation, Riemannian Motion Policies, Wavemap, Volumetric mapping, Mobile robots","lastPublishedDoi":"10.21203/rs.3.rs-9564893/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-9564893/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eAutonomous exploration requires local navigation that reacts to newly observed geometry under strict runtime constraints while respecting non-holonomic motion. 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