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Robotics
Other literature type . 2019
License: CC BY
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Robotics
Article . 2019 . Peer-reviewed
License: CC BY
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Robotics
Article
License: CC BY
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Robotics
Article . 2019
Data sources: DOAJ
DBLP
Article . 2019
Data sources: DBLP
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Wearable Sensors for Human–Robot Walking Together

Authors: Moschetti, Alessandra; Cavallo, Filippo; Esposito, Dario; Penders, Jacques; Di Nuovo, Alessandro;

Wearable Sensors for Human–Robot Walking Together

Abstract

Thanks to recent technological improvements that enable novel applications beyond the industrial context, there is growing interest in the use of robots in everyday life situations. To improve the acceptability of personal service robots, they should seamlessly interact with the users, understand their social signals and cues and respond appropriately. In this context, a few proposals were presented to make robots and humans navigate together naturally without explicit user control, but no final solution has been achieved yet. To make an advance toward this end, this paper proposes the use of wearable Inertial Measurement Units to improve the interaction between human and robot while walking together without physical links and with no restriction on the relative position between the human and the robot. We built a prototype system, experimented with 19 human participants in two different tasks, to provide real-time evaluation of gait parameters for a mobile robot moving together with a human, and studied the feasibility and the perceived usability by the participants. The results show the feasibility of the system, which obtained positive feedback from the users, giving valuable information for the development of a natural interaction system where the robot perceives human movements by means of wearable sensors.

Country
Italy
Keywords

motion analysis, Human-robot interaction; Inertial wearable sensors; Motion analysis; Social robots, TJ1-1570, human–robot interaction, Mechanical engineering and machinery, social robots, inertial wearable sensors

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    12
    popularity
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    Top 10%
    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
12
Top 10%
Average
Top 10%
Green
gold