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waveSLAM: Empowering accurate indoor mapping using off-the-shelf millimeter-wave self-sensing

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dc.affiliation.dptoUC3M. Departamento de Ingeniería Telemáticaes
dc.affiliation.grupoinvUC3M. Grupo de Investigación: Network Technologieses
dc.contributor.authorPicazo Martinez, Pablo
dc.contributor.authorGroshev, Milan
dc.contributor.authorOliva Delgado, Antonio de la
dc.contributor.funderEuropean Commissionen
dc.contributor.funderMinisterio de Economía y Competitividad (España)es
dc.date.accessioned2023-11-20T15:23:32Z
dc.date.available2023-11-20T15:23:32Z
dc.date.issued2023-11-20
dc.descriptionProceedings of: 2023 IEEE 98th Vehicular Technology Conference: VTC2023-Fall, 10-13 October 2023, Hong Kong.en
dc.description.abstractThis paper presents the design, implementation and evaluation of waveSLAM, a low-cost mobile robot system that uses the millimetre wave (mmWave) communication devices to enhance the indoor mapping process targeting environments with reduced visibility or glass/mirror walls. A unique feature of waveSLAM is that it only leverages existing Commercial-Off-The-Shelf (COTS) hardware (Lidar and mmWave radios) that are mounted on mobile robots to improve the accurate indoor mapping achieved with optical sensors. The key intuition behind the waveSLAM design is that while the mobile robots moves freely, the mmWave radios can periodically exchange angle and distance estimates between themselves (self-sensing) by bouncing the signal from the environment, thus enabling accurate estimates of the target object/material surface. Our experiments verify that waveSLAM can archive cm-level accuracy with errors below 22 cm and 20◦ in angle orientation which is compatible with Lidar when building indoor maps.en
dc.description.sponsorshipThis work has been partially funded by the European Union's Horizon Europe research and innovation program under grant agreement No 101095759 (Hexa-X-II) and the Spanish Ministry of Economic Affairs and Digital Transformation and the European Union-Next Generation EU through the UNICO 5G I+D 6G-EDGEDT.en
dc.format.extent7
dc.identifier.bibliographicCitationPicazo, P, Groshev, M., Blanco, A., Fiandrino, C., de la Oliva, A. & Widmer, J. (10-13 October 2023). waveSLAM: empowering accurate indoor mapping using off-the-shelf millimeter-wave self-sensing [proceedings]. 2023 IEEE 98th Vehicular Technology Conference: VTC2023-Fall, Hong Kong.en
dc.identifier.publicationfirstpage1
dc.identifier.publicationlastpage7
dc.identifier.urihttps://hdl.handle.net/10016/38916
dc.identifier.uxxiCC/0000034559
dc.language.isoengen
dc.relation.eventdate2023-10-10
dc.relation.eventplaceCHINAes
dc.relation.eventtitle2023 IEEE 98th Vehicular Technology Conference: VTC2023-Fallen
dc.relation.projectIDGobierno de España. TSI-063000-2021-117es
dc.relation.projectIDinfo:eu-repo/grantAgreement/EC/101095759en
dc.rights© 2023 IEEE.en
dc.rights.accessRightsopen accessen
dc.subject.ecienciaTelecomunicacioneses
dc.subject.otherIndoor mappingen
dc.subject.otherMmWave sensingen
dc.subject.other60 GHzen
dc.subject.otherSelfsensingen
dc.subject.otherBeamsweepingen
dc.subject.otherFTMen
dc.subject.otherCSIen
dc.titlewaveSLAM: Empowering accurate indoor mapping using off-the-shelf millimeter-wave self-sensingen
dc.typeconference poster*
dc.type.hasVersionAM*
dspace.entity.typePublication
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