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Automated USMN integration for precision robotics and large-scale metrology

dc.contributor.authorAsif, Seemal
dc.contributor.authorIzuwa, Emmanuel
dc.contributor.authorSawyer, Daniela
dc.contributor.authorBurkinshaw, Christopher
dc.date.accessioned2025-09-10T11:19:59Z
dc.date.available2025-09-10T11:19:59Z
dc.date.freetoread2025-09-10
dc.date.issued2026-08-13
dc.date.pubOnline2025-08-13
dc.description.abstractThis study introduces a novel automation framework for the integration of the Unified Spatial Metrology Network (USMN) across Spatial Analyzer (SA) and PolyWorks (PW), addressing critical inefficiencies in manual metrology workflows. Traditional methods for USMN execution and data translation between platforms are labor-intensive, error-prone, and time-consuming. The proposed system automates data transfer, reference point alignment, and coordinate calibration, incorporating real-time error detection to ensure spatial coherence and enhance measurement accuracy. This approach significantly reduces processing time from days to minutes, mitigates human error, and standardizes inter-software interoperability, while maintaining residual RMS error within ≤0.02 mm. Application of this framework to large-scale robotic systems—common in aerospace, shipbuilding, and automotive manufacturing—demonstrates improved precision in automated tasks such as assembly, drilling, and alignment. By enabling seamless integration of multiple spatial instruments, the framework enhances the robustness and repeatability of high-precision measurements. This advancement represents a pivotal contribution to metrology automation and scalable, real-time calibration in complex industrial environments.
dc.description.bookTitleLecture Notes in Computer Science
dc.description.conferencenameTowards Autonomous Robotic Systems (TAROS 2025)
dc.description.sponsorshipThis work part of a collaboration with AMRC Sheffield, funded by the Engineering and Physical Sciences Research Council's Innovation Launchpad Network+ Researcher in Residence scheme, grant numbers EP/W037009/1 & EP/X528493/1.
dc.format.extentpp. 68-79
dc.identifier.citationAsif S, Izuwa E, Sawyer D, Burkinshaw C. (2026) Automated USMN integration for precision robotics and large-scale metrology. In: Towards Autonomous Robotic Systems: TAROS 2025, 20-22 August 2025, York, UK, Volume 16045 Lecture Notes in Computer Science, pp. 68-79en_UK
dc.identifier.elementsID862913
dc.identifier.isbn9783032014856
dc.identifier.issn0302-9743
dc.identifier.urihttps://doi.org/10.1007/978-3-032-01486-3_7
dc.identifier.urihttps://dspace.lib.cranfield.ac.uk/handle/1826/24400
dc.identifier.volumeNo16045
dc.language.isoen
dc.publisherSpringeren_UK
dc.publisher.urihttps://link.springer.com/chapter/10.1007/978-3-032-01486-3_7
dc.relation.ispartofseriesLecture Notes in Computer Science
dc.rightsAttribution 4.0 Internationalen
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/
dc.subjectNetworking and Information Technology R&D (NITRD)en_UK
dc.subjectArtificial Intelligence & Image Processingen_UK
dc.subject46 Information and computing sciencesen_UK
dc.subjectUnified Spatial Metrology Network (USMN)en_UK
dc.subjectSpatial Analyzeren_UK
dc.subjectPolyWorksen_UK
dc.subjectMetrology Automationen_UK
dc.subjectMeasurement Accuracyen_UK
dc.subjectReference Point Calibrationen_UK
dc.subjectCoordinate System Normalisationen_UK
dc.subjectLaser Trackeren_UK
dc.subjectHigh-Precision Metrologyen_UK
dc.subjectLarge-Scale Engineeringen_UK
dc.subjectRobotic Automationen_UK
dc.titleAutomated USMN integration for precision robotics and large-scale metrologyen_UK
dc.typeConference paper
dcterms.coverageYork, UK
dcterms.dateAccepted2025-05-19
dcterms.temporal.endDate22-Aug-2025
dcterms.temporal.startDate20-Aug-2025

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