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Bluetooth low energy for autonomous human-robot interaction

dc.contributor.authorScheunemann, Marcus M.
dc.contributor.authorDautenhahn, Kerstin
dc.date.accessioned2019-10-12T00:01:55Z
dc.date.available2019-10-12T00:01:55Z
dc.date.issued2017-03-06
dc.identifier.citationScheunemann , M M & Dautenhahn , K 2017 , Bluetooth low energy for autonomous human-robot interaction . in Proceedings of the Companion of the 2017 ACM/IEEE International Conference on Human-Robot Interaction . IEEE Computer Society , pp. 52 , 12th Annual ACM/IEEE International Conference on Human-Robot Interaction, HRI 2017 , Vienna , Austria , 6/03/17 . https://doi.org/10.1145/3029798.3036663
dc.identifier.citationconference
dc.identifier.isbn9781450348850
dc.identifier.otherORCID: /0000-0002-0815-7024/work/63007865
dc.identifier.urihttp://hdl.handle.net/2299/21733
dc.description© 2017 Copyright held by the owner/author(s).
dc.description.abstractThis demonstration shows how inexpensive, off-the-shelf, and unobtrusive Bluetooth Low Energy (BLE) devices can be utilized for enabling robots to recognize touch gestures, to perceive proximity information, and to distinguish between interacting individuals autonomously. The received signal strength (RSS) between the BLE device attached to the robot and BLE devices attached to the interacting individuals is used to achieve this. Almost no software configuration is needed and the setup can be applied to most everyday environments and robot platforms.en
dc.format.extent1
dc.format.extent141691
dc.language.isoeng
dc.publisherIEEE Computer Society
dc.relation.ispartofProceedings of the Companion of the 2017 ACM/IEEE International Conference on Human-Robot Interaction
dc.subjectautonomous interaction
dc.subjectbluetooth low energy
dc.subjecthuman-robot interaction
dc.subjectproxemics
dc.subjectrobot design
dc.subjectArtificial Intelligence
dc.subjectHuman-Computer Interaction
dc.subjectElectrical and Electronic Engineering
dc.titleBluetooth low energy for autonomous human-robot interactionen
dc.contributor.institutionAdaptive Systems
dc.contributor.institutionECS Computer Science VLs
dc.contributor.institutionDepartment of Computer Science
dc.contributor.institutionSchool of Physics, Engineering & Computer Science
dc.contributor.institutionSchool of Computer Science
dc.contributor.institutionCentre for Computer Science and Informatics Research
dc.identifier.urlhttp://www.scopus.com/inward/record.url?scp=85016417792&partnerID=8YFLogxK
rioxxterms.versionofrecord10.1145/3029798.3036663
rioxxterms.typeOther
herts.preservation.rarelyaccessedtrue


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