Collision Avoidance Maneuver Planning and Optimization Considering Control Uncertainty and Mission Requirements

preprint OA: closed
Full text JSON View at publisher
AI-generated summary by claude@2026-07, 2026-07-16

This paper presents a two-step framework for collision avoidance maneuver planning that quantifies trade-offs among objectives and optimizes maneuvers considering control uncertainty and mission-specific constraints.

One-sentence paraphrase of the abstract; not a substitute for reading it. No clinical advice. How this works

AI-generated deep summary by claude@2026-07, 2026-07-16 · read from full text

This paper studies collision avoidance maneuver planning for active satellites under control and propulsion performance uncertainty, using a two-step NorthStar framework that first solves a multi-objective problem to quantify trade-offs among maneuver-related objectives and then formulates an optimal control problem. The optimization is posed to satisfy high-fidelity dynamics and mission-specific constraints while incorporating stochastic and deterministic miss-distance safety considerations, with explicit attention to uncertainty in propulsion system performance and other potential disruptions. The framework additionally accounts for orbit maintenance maneuvers and GEO slot adherence, and is tested using case studies based on CDMs. A key caveat stated in the preprint is that it has not been peer reviewed. The paper does not explicitly discuss endometriosis or adenomyosis; it was included in the corpus via a keyword match in the upstream search index.

Read from the paper's body, not the abstract. Not a substitute for reading the paper. No clinical advice. How this works

Abstract

Abstract The rise in space traffic congestion has made collision avoidance maneuvers a crucial mode to ensure real-time safety of active satellites. However, performing a collision avoidance maneuver involves the usage of limited on-orbit fuel, losing mission time, incurring operational costs, etc. Therefore, the workload associated with conjunction analysis, the decision on the need to perform a collision avoidance maneuver, and, where appropriate, its design, has increased significantly. In this line, NorthStar has developed a two-step framework for both the decision-making and the design process of a collision avoidance maneuver. In the first step, a multi-objective problem is solved to identify the quantitative trade-offs among the various objectives. Once the suitable maneuver strategy has been identified, an optimal control problem is posed, the solution of which is compliant with high-fidelity dynamics and mission-specific constraints with the possibility of addressing additional safety considerations on top of respecting the stochastic and deterministic miss distance. These can include incorporating the effects of control uncertainty in the trajectory design alongside ensuring consideration for any unforeseen disruption of the propulsion system. The solution is also designed to incorporate orbit maintenance maneuvers and adhere to allotted GEO slots when necessary. The framework has been tested with case studies using CDMs. This paper presents the validation results of the system with emphasis on incorporating uncertainty on the propulsion system performance.
Full text 12,180 characters · extracted from preprint-html · click to expand
Collision Avoidance Maneuver Planning and Optimization Considering Control Uncertainty and Mission Requirements | 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 Collision Avoidance Maneuver Planning and Optimization Considering Control Uncertainty and Mission Requirements Shrouti Dutta, Matteo Budoni, Guillermo Escribano, Priyatharsan Rajasekar, and 3 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8811380/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 The rise in space traffic congestion has made collision avoidance maneuvers a crucial mode to ensure real-time safety of active satellites. However, performing a collision avoidance maneuver involves the usage of limited on-orbit fuel, losing mission time, incurring operational costs, etc. Therefore, the workload associated with conjunction analysis, the decision on the need to perform a collision avoidance maneuver, and, where appropriate, its design, has increased significantly. In this line, NorthStar has developed a two-step framework for both the decision-making and the design process of a collision avoidance maneuver. In the first step, a multi-objective problem is solved to identify the quantitative trade-offs among the various objectives. Once the suitable maneuver strategy has been identified, an optimal control problem is posed, the solution of which is compliant with high-fidelity dynamics and mission-specific constraints with the possibility of addressing additional safety considerations on top of respecting the stochastic and deterministic miss distance. These can include incorporating the effects of control uncertainty in the trajectory design alongside ensuring consideration for any unforeseen disruption of the propulsion system. The solution is also designed to incorporate orbit maintenance maneuvers and adhere to allotted GEO slots when necessary. The framework has been tested with case studies using CDMs. This paper presents the validation results of the system with emphasis on incorporating uncertainty on the propulsion system performance. Control uncertainty Mission compliance Non-linear programming Collision Avoidance 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-8811380","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":610250552,"identity":"5e5f945f-47e6-4028-94a2-d2a16b3aeb82","order_by":0,"name":"Shrouti Dutta","email":"data:image/png;base64,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","orcid":"","institution":"NorthStar Earth and Space","correspondingAuthor":true,"prefix":"","firstName":"Shrouti","middleName":"","lastName":"Dutta","suffix":""},{"id":610250553,"identity":"c28f1e53-7d3f-456f-9f0a-17663fb7a325","order_by":1,"name":"Matteo Budoni","email":"","orcid":"","institution":"NorthStar Earth and Space","correspondingAuthor":false,"prefix":"","firstName":"Matteo","middleName":"","lastName":"Budoni","suffix":""},{"id":610250559,"identity":"34015b4f-fc52-42c5-9298-c269c9132030","order_by":2,"name":"Guillermo Escribano","email":"","orcid":"","institution":"NorthStar Earth and Space","correspondingAuthor":false,"prefix":"","firstName":"Guillermo","middleName":"","lastName":"Escribano","suffix":""},{"id":610250560,"identity":"fc3bcb84-4d4a-4395-8961-bf4e631c6877","order_by":3,"name":"Priyatharsan Rajasekar","email":"","orcid":"","institution":"NorthStar Earth and Space","correspondingAuthor":false,"prefix":"","firstName":"Priyatharsan","middleName":"","lastName":"Rajasekar","suffix":""},{"id":610250561,"identity":"573af5e4-1e49-4504-8b27-1bfce7812782","order_by":4,"name":"Laura Pirovano","email":"","orcid":"","institution":"NorthStar Earth and Space","correspondingAuthor":false,"prefix":"","firstName":"Laura","middleName":"","lastName":"Pirovano","suffix":""},{"id":610250569,"identity":"a4bb58d1-76c2-4a1d-b8cc-16e4eb9e5f8f","order_by":5,"name":"Manuel Sanjurjo-Rivo","email":"","orcid":"","institution":"NorthStar Earth and Space","correspondingAuthor":false,"prefix":"","firstName":"Manuel","middleName":"","lastName":"Sanjurjo-Rivo","suffix":""},{"id":610250570,"identity":"fc75cae9-2888-4a20-b1b0-b86fce82a6c1","order_by":6,"name":"Yann Picard","email":"","orcid":"","institution":"NorthStar Earth and Space","correspondingAuthor":false,"prefix":"","firstName":"Yann","middleName":"","lastName":"Picard","suffix":""}],"badges":[],"createdAt":"2026-02-07 00:53:03","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-8811380/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-8811380/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":105564968,"identity":"78a87478-ed1a-40f2-b8a5-1943509f92bd","added_by":"auto","created_at":"2026-03-27 12:51:29","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":690569,"visible":true,"origin":"","legend":"","description":"","filename":"ShroutietalCAMPlanningandOptimizationConsideringControlUncertainty.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8811380/v1_covered_77ba3079-9f40-4ff9-ba8b-88c1d7b2c1ce.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Collision Avoidance Maneuver Planning and Optimization Considering Control Uncertainty and Mission Requirements","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":"Control uncertainty, Mission compliance, Non-linear programming, Collision Avoidance","lastPublishedDoi":"10.21203/rs.3.rs-8811380/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8811380/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"The rise in space traffic congestion has made collision avoidance maneuvers a crucial mode to ensure real-time safety of active satellites. However, performing a collision avoidance maneuver involves the usage of limited on-orbit fuel, losing mission time, incurring operational costs, etc. Therefore, the workload associated with conjunction analysis, the decision on the need to perform a collision avoidance maneuver, and, where appropriate, its design, has increased significantly. In this line, NorthStar has developed a two-step framework for both the decision-making and the design process of a collision avoidance maneuver. In the first step, a multi-objective problem is solved to identify the quantitative trade-offs among the various objectives. Once the suitable maneuver strategy has been identified, an optimal control problem is posed, the solution of which is compliant with high-fidelity dynamics and mission-specific constraints with the possibility of addressing additional safety considerations on top of respecting the stochastic and deterministic miss distance. These can include incorporating the effects of control uncertainty in the trajectory design alongside ensuring consideration for any unforeseen disruption of the propulsion system. The solution is also designed to incorporate orbit maintenance maneuvers and adhere to allotted GEO slots when necessary. The framework has been tested with case studies using CDMs. This paper presents the validation results of the system with emphasis on incorporating uncertainty on the propulsion system performance.","manuscriptTitle":"Collision Avoidance Maneuver Planning and Optimization Considering Control Uncertainty and Mission Requirements","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-03-24 20:31:02","doi":"10.21203/rs.3.rs-8811380/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","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}}],"origin":"","ownerIdentity":"97e36e95-6189-4ce6-8894-c97a3a207dde","owner":[],"postedDate":"March 24th, 2026","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2026-04-22T14:11:04+00:00","versionOfRecord":[],"versionCreatedAt":"2026-03-24 20:31:02","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-8811380","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8811380","identity":"rs-8811380","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}

Text is read by the "Ask this paper" AI Q&A widget below. Extraction quality varies by source — PMC NXML preserves structure cleanly, OA-HTML may include some navigation residue, and OA-PDF can have broken hyphenation. The publisher copy (via DOI) is the canonical version.

My notes (saved in your browser only)

Ask this paper AI returns verbatim quotes from the full text · source: preprint-html

Answers must be backed by verbatim quotes from this paper's full text. Hallucinated quotes are dropped automatically; if no verbatim passage answers the question, we say so. How this works

Citation neighborhood (no data yet)

We don't have any in-corpus citations linked to this paper yet. This is a recent paper (2026) — citers typically take a year or two to land, and the OpenAlex reference graph may still be filling in.

Source provenance

europepmc
last seen: 2026-05-20T01:45:00.602351+00:00