Commit 843b11d5 authored by Marcus M. Scheunemann's avatar Marcus M. Scheunemann

add arXiv identifier and change author formatting

parent b39f85a2
Pipeline #56107966 passed with stages
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......@@ -52,21 +52,23 @@
}
@InProceedings{ScheunemannDautenhahnEtAl-16,
author = {Scheunemann, Marcus M and Dautenhahn, Kerstin and Salem, Maha and Robins, Ben},
title = {{Utilizing Bluetooth Low Energy to recognize proximity, touch and humans}},
booktitle = {2016 25th IEEE International Symposium on Robot and Human Interactive Communication (RO-MAN)},
year = {2016},
pages = {362--367},
month = {Aug},
publisher = {IEEE},
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.},
doi = {10.1109/ROMAN.2016.7745156},
issn = {1944-9437},
keywords = {Bluetooth;human-robot interaction;mobile robots;tactile sensors;BLE devices;HRI experiments;RSS;adaptive behavior;configurable technique;cost intensive task;human inhabited environment;human-robot interaction;humans;inexpensive bluetooth low energy;mobile spherical robots;noisy laboratory setting;proximity information;raw received signal strength;recognize proximity;sensor system;touch sensor;Bluetooth;Cameras;Mobile robots;Robot vision systems;Tactile sensors},
location = {New York, NY, USA},
tags = {Conferences},
timestamp = {2017.10.13},
pdf = {/publications/2016-Utilizing-Bluetooth-Low-Energy-to-recognize-proximity-touch-and-humans.pdf},
author = {Marcus M. Scheunemann and Kerstin Dautenhahn and Maha Salem and Ben Robins},
title = {{Utilizing Bluetooth Low Energy to recognize proximity, touch and humans}},
booktitle = {2016 25th IEEE International Symposium on Robot and Human Interactive Communication (RO-MAN)},
year = {2016},
pages = {362--367},
month = {Aug},
publisher = {IEEE},
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.},
archiveprefix = {arXiv},
doi = {10.1109/ROMAN.2016.7745156},
eprint = {1904.03475},
issn = {1944-9437},
keywords = {Bluetooth;human-robot interaction;mobile robots;tactile sensors;BLE devices;HRI experiments;RSS;adaptive behavior;configurable technique;cost intensive task;human inhabited environment;human-robot interaction;humans;inexpensive bluetooth low energy;mobile spherical robots;noisy laboratory setting;proximity information;raw received signal strength;recognize proximity;sensor system;touch sensor;Bluetooth;Cameras;Mobile robots;Robot vision systems;Tactile sensors},
location = {New York, NY, USA},
pdf = {/publications/2016-Utilizing-Bluetooth-Low-Energy-to-recognize-proximity-touch-and-humans.pdf},
tags = {Conferences},
timestamp = {2019.04.10},
}
@InProceedings{ScheunemannDautenhahn-17,
......@@ -94,7 +96,7 @@
}
@InProceedings{ScheunemannDautenhahnEtAl-16b,
author = {Scheunemann, Marcus M and Dautenhahn, Kerstin and Salem, Maha and Robins, Ben},
author = {Marcus M. Scheunemann and Kerstin Dautenhahn and Maha Salem and Ben Robins},
title = {{Utilizing Bluetooth Low Energy for human-robot interaction}},
booktitle = {2016 25th IEEE International Symposium on Robot and Human Interactive Communication (RO-MAN)},
year = {2016},
......@@ -106,9 +108,9 @@
location = {New York, NY, USA},
numpages = {1},
owner = {scheunemann},
pdf = {/publications/2016-Utilizing-Bluetooth-Low-Energy-for-human-robot-interaction.pdf},
tags = {Conferences},
timestamp = {2017.10.13},
pdf = {/publications/2016-Utilizing-Bluetooth-Low-Energy-for-human-robot-interaction.pdf}
}
@Comment{jabref-meta: databaseType:bibtex;}
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