Towards the quantification of human-robot imitation using wearable inertial sensors

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

Authors

Colleges, School and Institutes

External organisations

  • Birmingham University
  • School of Electronics
  • University of Oulu

Abstract

In this study, we propose a metric in order to quantify how closely a healthy participant imitates a robot, for which we use inertial sensors attached to both individual participant and to a humanoid-robot. For the experiment, twelve healthy participants were invited to perform simple arm movements in order to apply the state space reconstruction which is based on the method of time-delay embedding and PCA. Although the performed arm movements of the healthy participants were very simple, the study reveals that the participants showed different ranges of the proposed metric that can be linked to the level of imitation. Such a metric can be improved in order to determine a detailed scoring of human-robot imitation during training or rehabilitation activities.

Details

Original languageEnglish
Title of host publicationHRI 2017 - Companion of the 2017 ACM/IEEE International Conference on Human-Robot Interaction
Publication statusPublished - 6 Mar 2017
Event12th Annual ACM/IEEE International Conference on Human-Robot Interaction, HRI 2017 - Vienna, Austria
Duration: 6 Mar 20179 Mar 2017

Publication series

NameACM/IEEE International Conference on Human-Robot Interaction
ISSN (Electronic)2167-2148

Conference

Conference12th Annual ACM/IEEE International Conference on Human-Robot Interaction, HRI 2017
CountryAustria
CityVienna
Period6/03/179/03/17

Keywords

  • human-robot imitation, movement variability, non-linear dynamics, state space reconstruction, wearable inertial sensors