University of Hertfordshire

By the same authors

Utilizing Bluetooth Low Energy to recognize proximity, touch and humans

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Documents

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Original languageEnglish
Title of host publication25th IEEE International Symposium on Robot and Human Interactive Communication, RO-MAN 2016
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages362-367
Number of pages6
ISBN (Electronic)9781509039296
DOIs
Publication statusPublished - 17 Nov 2016
Event25th IEEE International Symposium on Robot and Human Interactive Communication, RO-MAN 2016 - New York, United States
Duration: 26 Aug 201631 Aug 2016

Publication series

Name25th IEEE International Symposium on Robot and Human Interactive Communication, RO-MAN 2016

Conference

Conference25th IEEE International Symposium on Robot and Human Interactive Communication, RO-MAN 2016
CountryUnited States
CityNew York
Period26/08/1631/08/16

Abstract

Interacting with humans is one of the main challenges for mobile robots in a human inhabited environment. To enable adaptive behavior, a robot needs to recognize touch gestures and/or the proximity to interacting individuals. Moreover, a robot interacting with two or more humans usually needs to distinguish between them. However, this remains both a configuration and cost intensive task. In this paper we utilize inexpensive Bluetooth Low Energy (BLE) devices and propose an easy and configurable technique to enhance the robot's capabilities to interact with surrounding people. In a noisy laboratory setting, a mobile spherical robot is utilized in three proof-of-concept experiments of the proposed system architecture. Firstly, we enhance the robot with proximity information about the individuals in the surrounding environment. Secondly, we exploit BLE to utilize it as a touch sensor. And lastly, we use BLE to distinguish between interacting individuals. Results show that observing the raw received signal strength (RSS) between BLE devices already enhances the robot's interaction capabilities and that the provided infrastructure can be facilitated to enable adaptive behavior in the future. We show one and the same sensor system can be used to detect different types of information relevant in human-robot interaction (HRI) experiments.

ID: 17414497