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 O'Murchu, Cian
dc.contributor.author Mathewson, Alan
dc.contributor.author Gnecchi, Salvatore
dc.contributor.author Buckley, Steve
dc.date.accessioned 2018-09-24T15:45:25Z
dc.date.available 2018-09-24T15:45:25Z
dc.date.issued 2018-04
dc.identifier.citation O'Keefe, R., O'Murchu, C., Mathewson, A., Gnecchi, S. and Buckley, S. (2018) 'Long range LiDAR characterisation for obstacle detection for use by the visually impaired and blind', Smart Systems Integration 2018, Dresden, Germany, 11-12 April. en
dc.identifier.startpage 1 en
dc.identifier.endpage 4 en
dc.identifier.uri http://hdl.handle.net/10468/6902
dc.description.abstract Obstacle detection has become a very important area of interest for the automotive industry due to the move towards autonomous vehicles. Since the environment the vehicle has to navigate is ever changing the current best system for obstacle detection is to combine a number of sensors. This means that for the varying weather and lighting conditions the best sensor can be used to provided obstacle detection and avoidance information. The INSPEX H2020 project goal is to use a similar system of multiple sensors to provide personal obstacle detection for visually impaired and blind (VIB) people. Figure 1 shows the INSPEX ambition. Power, weight and size reduction will be key to achieving this goal. In this paper the initial prototype is characterised and improvements beyond typical reduction of key parameters is considered. The INSPEX system will integrate a short range LiDAR (distances up to 5m), an ultrawide band (UWB) RADAR (distances up to 5m), ultrasound (distances up to 2m) and a long range LiDAR (distances up to 10m). The sensors will be miniaturised and the power consumption reduced so that they can be incorporated into a white cane. In this paper the first prototype for the long range LiDAR sensor is characterised for various lighting conditions and distances. The results show that for distances of 3m and 5m consistence obstacle detection can be achieved even in bright lighting conditions but for distances beyond this the detection can be inconsistence and is highly dependent on the lighting conditions. 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.description.uri https://ssi.mesago.com/events/en.html en
dc.format.mimetype application/pdf en
dc.language.iso en en
dc.relation.ispartof Smart Systems Integration 2018
dc.relation.uri https://www.smart-systems-integration.org/public/news-events/events/ssi-2018
dc.rights © 2018 the authors. 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 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 2018-09-24T15:31:01Z
dc.description.version Accepted Version en
dc.internal.rssid 454961535
dc.contributor.funder Horizon 2020 en
dc.contributor.funder Staatssekretariat für Bildung, Forschung und Innovation en
dc.description.status Peer reviewed en
dc.internal.copyrightchecked No !!CORA!! en
dc.internal.licenseacceptance Yes en
dc.internal.conferencelocation Dresden, Germany en
dc.internal.IRISemailaddress cian.omurchu@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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