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Main Authors: Mishra, Ruchik, Welch, Karla Conn
Format: Preprint
Published: 2023
Subjects:
Online Access:https://arxiv.org/abs/2307.01309
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author Mishra, Ruchik
Welch, Karla Conn
author_facet Mishra, Ruchik
Welch, Karla Conn
contents The social applications of robots possess intrinsic challenges with respect to social paradigms and heterogeneity of different groups. These challenges can be in the form of social acceptability, anthropomorphism, likeability, past experiences with robots etc. In this paper, we have considered a group of neurotypical adults to describe how different voices and motion types of the NAO robot can have effect on the perceived safety, anthropomorphism, likeability, animacy, and perceived intelligence of the robot. In addition, prior robot experience has also been taken into consideration to perform this analysis using a one-way Analysis of Variance (ANOVA). Further, we also demonstrate that these different modalities instigate different physiological responses in the person. This classification has been done using two different deep learning approaches, 1) Convolutional Neural Network (CNN), and 2) Gramian Angular Fields on the Blood Volume Pulse (BVP) data recorded. Both of these approaches achieve better than chance accuracy 25% for a 4 class classification.
format Preprint
id arxiv_https___arxiv_org_abs_2307_01309
institution arXiv
publishDate 2023
record_format arxiv
spellingShingle Social Impressions of the NAO Robot and its Impact on Physiology
Mishra, Ruchik
Welch, Karla Conn
Robotics
The social applications of robots possess intrinsic challenges with respect to social paradigms and heterogeneity of different groups. These challenges can be in the form of social acceptability, anthropomorphism, likeability, past experiences with robots etc. In this paper, we have considered a group of neurotypical adults to describe how different voices and motion types of the NAO robot can have effect on the perceived safety, anthropomorphism, likeability, animacy, and perceived intelligence of the robot. In addition, prior robot experience has also been taken into consideration to perform this analysis using a one-way Analysis of Variance (ANOVA). Further, we also demonstrate that these different modalities instigate different physiological responses in the person. This classification has been done using two different deep learning approaches, 1) Convolutional Neural Network (CNN), and 2) Gramian Angular Fields on the Blood Volume Pulse (BVP) data recorded. Both of these approaches achieve better than chance accuracy 25% for a 4 class classification.
title Social Impressions of the NAO Robot and its Impact on Physiology
topic Robotics
url https://arxiv.org/abs/2307.01309