Long range LiDAR characterisation for obstacle detection for use by the visually impaired and blind

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dc.contributor.author O'Keeffe, Rosemary
dc.contributor.author Gnecchi, Salvatore
dc.contributor.author Buckley, Steve
dc.contributor.author O'Murchu, Cian
dc.contributor.author Mathewson, Alan
dc.contributor.author Lesecq, Suzanne
dc.contributor.author Foucault, Julie
dc.date.accessioned 2018-09-24T15:06:47Z
dc.date.available 2018-09-24T15:06:47Z
dc.date.issued 2018-06
dc.identifier.citation O’Keeffe, R., Gnecchi, S., Buckley, S., O’Murchu, C., Mathewson, A., Lesecq, S. and Foucault, J. (2018) 'Long Range LiDAR Characterisation for Obstacle Detection for use by the Visually Impaired and Blind', 2018 IEEE 68th Electronic Components and Technology Conference (ECTC), San Diego, CA, USA, 29 May-1 June 2018, pp. 533-538. doi: 10.1109/ECTC.2018.00084 en
dc.identifier.startpage 533 en
dc.identifier.endpage 538 en
dc.identifier.isbn 978-1-5386-4999-2
dc.identifier.isbn 978-1-5386-5000-4
dc.identifier.issn 2377-5726
dc.identifier.uri http://hdl.handle.net/10468/6901
dc.identifier.doi 10.1109/ECTC.2018.00084
dc.description.abstract Obstacle detection and avoidance is a huge area of interest for autonomous vehicles and, as such, has become an important research topic. Detecting and identifying obstacles enables navigation through an ever changing environment. This work looks at the technology used in self-driving vehicles and examines whether the same technology could be used to aid in navigation for visually impaired and blind (VIB) people. For autonomous vehicles, obstacle detection relies on different sensor modalities to provide information on the vehicles surroundings. A combination of the same sensors placed on a white cane could be used to perform free-space assessment over the whole height of the user and provide additional environmental information not available from the cane alone. This provides its own challenges and advantages. The speeds are much slower when dealing with pedestrians and scanning can be achieved by the movement of the cane. However, the weight and size must be significantly reduced. The full system will be integrated into a smart cane and will consist of four main sensors as well as range sensors. The aim of this work is to report on the characterisation of a long range LiDAR (up to 10m) that will be integrated into a smart white cane developed as part of the INSPEX H2020 project. en
dc.description.sponsorship Staatssekretariat für Bildung, Forschung und Innovation (Swiss Secretariat for Education, Research and Innovation (SERI) under Grant 16.0136 730953) en
dc.format.mimetype application/pdf en
dc.language.iso en en
dc.publisher Institute of Electrical and Electronics Engineers (IEEE) en
dc.relation.ispartof 2018 IEEE 68th Electronic Components and Technology Conference (ECTC)
dc.relation.uri https://ieeexplore.ieee.org/abstract/document/8429597
dc.rights © 2018 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. en
dc.subject Collision avoidance en
dc.subject Handicapped aids en
dc.subject Mobile robots en
dc.subject Optical radar en
dc.subject Ultrasonic devices en
dc.subject Range LiDAR characterisation en
dc.subject Obstacle detection en
dc.subject Autonomous vehicles en
dc.subject Vehicles surroundings en
dc.subject Range sensors en
dc.subject Smart white cane en
dc.subject Visually impaired and blind people en
dc.subject Size 10.0 m en
dc.subject Laser radar en
dc.subject Sensor systems en
dc.subject Sensor phenomena and characterization en
dc.subject Intelligent sensors en
dc.subject Prototypes en
dc.subject Sensor arrays en
dc.subject LiDAR en
dc.subject Characterisation en
dc.subject Embedded en
dc.subject Integrated system en
dc.subject Low-power en
dc.title Long range LiDAR characterisation for obstacle detection for use by the visually impaired and blind en
dc.type Conference item en
dc.internal.authorcontactother Rosemary O'Keefe, Tyndall Microsystems, University College Cork, Cork, Ireland. +353-21-490-3000 Email: rosemary.okeefe@tyndall.ie en
dc.internal.availability Full text available en
dc.date.updated 2018-09-24T14:49:13Z
dc.description.version Accepted Version en
dc.internal.rssid 454961532
dc.contributor.funder Horizon 2020 en
dc.contributor.funder Staatssekretariat für Bildung, Forschung und Innovation en
dc.description.status Peer reviewed en
dc.identifier.journaltitle 2018 IEEE 68th Electronic Components and Technology Conference (ECTC en
dc.internal.copyrightchecked No !!CORA!! en
dc.internal.licenseacceptance Yes en
dc.internal.conferencelocation San Diego, CA, USA en
dc.internal.IRISemailaddress rosemary.okeefe@tyndall.ie en
dc.relation.project info:eu-repo/grantAgreement/EC/H2020::RIA/730953/EU/Integrated Smart Spatial Exploration System/INSPEX en

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