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dc.contributor.authorGyrichidi, N.en
dc.contributor.authorRomanov, A. M.en
dc.contributor.authorTrofimov, O. V.en
dc.contributor.authorEroshenko, S. A.en
dc.contributor.authorMatrenin, P. V.en
dc.contributor.authorKhalyasmaa, A. I.en
dc.date.accessioned2025-02-25T10:52:07Z-
dc.date.available2025-02-25T10:52:07Z-
dc.date.issued2024-
dc.identifier.citationGyrichidi, N., Romanov, A. M., Trofimov, O. V., Eroshenko, S. A., Matrenin, P. V., & Khalyasmaa, A. I. (2024). GNSS-Based Narrow-Angle UV Camera Targeting: Case Study of a Low-Cost MAD Robot. Sensors, 24(11), [3494]. https://doi.org/10.3390/s24113494apa_pure
dc.identifier.issn1424-8220-
dc.identifier.otherFinal2
dc.identifier.otherAll Open Access; Gold Open Access; Green Open Access3
dc.identifier.otherhttps://www.scopus.com/inward/record.uri?eid=2-s2.0-85195882566&doi=10.3390%2fs24113494&partnerID=40&md5=0477003f17f0f71e7f0f7e5b680294391
dc.identifier.otherhttps://www.mdpi.com/1424-8220/24/11/3494/pdf?version=1716913085pdf
dc.identifier.urihttp://elar.urfu.ru/handle/10995/141660-
dc.description.abstractOne of the key challenges in Multi-Spectral Automatic Diagnostic (MAD) robot design is the precise targeting of narrow-angle cameras on a specific part of the equipment. The paper shows that a low-cost MAD robot, whose navigation system is based on open-source ArduRover firmware and a pair of low-cost Ublox F9P GNSS receivers, can inspect the 8 × 4 degree ultraviolet camera bounding the targeting error within 0.5 degrees. To achieve this result, we propose a new targeting procedure that can be implemented without any modifications in ArduRover firmware and outperforms more expensive solutions based on LiDAR SLAM and UWB. This paper will be interesting to the developers of robotic systems for power equipment inspection because it proposes a simple and effective solution for MAD robots’ camera targeting and provides the first quantitative analysis of the GNSS reception conditions during power equipment inspection. This analysis is based on the experimental results collected during the inspection of the overhead power transmission lines and equipment inspections on the open switchgear of different power plants. Moreover, it includes not only satellite, dilution of precision, and positioning/heading estimation accuracy but also the direct measurements of angular errors that could be achieved on operating power plants using GNSS-only camera targeting. © 2024 by the authors.en
dc.description.sponsorshipRussian Science Foundation, RSF, (22-79-10315); Russian Science Foundation, RSFen
dc.description.sponsorshipThis work was supported by the Russian Science Foundation, research project No. 22-79-10315.en
dc.format.mimetypeapplication/pdfen
dc.language.isoenen
dc.publisherMultidisciplinary Digital Publishing Institute (MDPI)en
dc.rightsinfo:eu-repo/semantics/openAccessen
dc.rightscc-byother
dc.sourceSensors2
dc.sourceSensorsen
dc.subjectCAMERA TARGETINGen
dc.subjectCORONA DISCHARGEen
dc.subjectENERGYen
dc.subjectGLOBAL NAVIGATION SATELLITE SYSTEMen
dc.subjectINSPECTIONen
dc.subjectPOWER TRANSMISSION LINEen
dc.subjectREAL-TIME KINEMATICen
dc.subjectSUBSTATIONen
dc.subjectUV SENSORSen
dc.subjectCOSTSen
dc.subjectELECTRIC POWER TRANSMISSIONen
dc.subjectELECTRIC SUBSTATIONSen
dc.subjectFIRMWAREen
dc.subjectINSPECTIONen
dc.subjectMACHINE DESIGNen
dc.subjectOVERHEAD LINESen
dc.subjectROBOTSen
dc.subjectAUTOMATIC DIAGNOSTICSen
dc.subjectCAMERA TARGETINGen
dc.subjectCORONA DISCHARGESen
dc.subjectENERGYen
dc.subjectGLOBAL NAVIGATION SATELLITE SYSTEMSen
dc.subjectMULTI-SPECTRALen
dc.subjectPOWER TRANSMISSION LINESen
dc.subjectREAL TIME KINEMATICen
dc.subjectSUBSTATIONen
dc.subjectUV SENSORen
dc.subjectARTICLEen
dc.subjectCAMERAen
dc.subjectCASE STUDYen
dc.subjectDILUTIONen
dc.subjectELECTRIC POWER PLANTen
dc.subjectENERGYen
dc.subjectGLOBAL NAVIGATION SATELLITE SYSTEMen
dc.subjectNAVIGATION SYSTEMen
dc.subjectQUANTITATIVE ANALYSISen
dc.subjectSENSORen
dc.subjectULTRAVIOLET RADIATIONen
dc.subjectCAMERASen
dc.titleGNSS-Based Narrow-Angle UV Camera Targeting: Case Study of a Low-Cost MAD Roboten
dc.typeArticleen
dc.typeinfo:eu-repo/semantics/articleen
dc.typeinfo:eu-repo/semantics/publishedVersionen
dc.identifier.doi10.3390/s24113494-
dc.identifier.scopus85195882566-
local.contributor.employeeGyrichidi N., Institute of Artificial Intelligence, MIREA—Russian Technological University (RTU MIREA), Moscow, 119454, Russian Federationen
local.contributor.employeeRomanov A.M., Institute of Artificial Intelligence, MIREA—Russian Technological University (RTU MIREA), Moscow, 119454, Russian Federationen
local.contributor.employeeTrofimov O.V., Institute of Artificial Intelligence, MIREA—Russian Technological University (RTU MIREA), Moscow, 119454, Russian Federationen
local.contributor.employeeEroshenko S.A., Ural Power Engineering Institute, Ural Federal University Named after the First President of Russia B.N. Yeltsin, Ekaterinburg, 620002, Russian Federationen
local.contributor.employeeMatrenin P.V., Ural Power Engineering Institute, Ural Federal University Named after the First President of Russia B.N. Yeltsin, Ekaterinburg, 620002, Russian Federation, Power Supply Systems Department, Novosibirsk State Technical University, Novosibirsk, 630073, Russian Federationen
local.contributor.employeeKhalyasmaa A.I., Ural Power Engineering Institute, Ural Federal University Named after the First President of Russia B.N. Yeltsin, Ekaterinburg, 620002, Russian Federationen
local.issue11-
local.volume24-
dc.identifier.wos001246373700001-
local.contributor.departmentInstitute of Artificial Intelligence, MIREA—Russian Technological University (RTU MIREA), Moscow, 119454, Russian Federationen
local.contributor.departmentUral Power Engineering Institute, Ural Federal University Named after the First President of Russia B.N. Yeltsin, Ekaterinburg, 620002, Russian Federationen
local.contributor.departmentPower Supply Systems Department, Novosibirsk State Technical University, Novosibirsk, 630073, Russian Federationen
local.identifier.pure58838941-
local.description.order3494
local.identifier.eid2-s2.0-85195882566-
local.fund.rsf22-79-10315
local.identifier.wosWOS:001246373700001-
local.identifier.pmid38894285-
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