Proceedings of the 7th International Conference on Education, Management, Information and Mechanical Engineering (EMIM 2017)

A Novel Design Approach for Facial Expression of Home Robot based on Kansei Engineering

Authors
Yunyun Wei, Huanzhi Lou
Corresponding Author
Yunyun Wei
Available Online April 2017.
DOI
10.2991/emim-17.2017.17How to use a DOI?
Keywords
Home robot; Facial expression; Kansei Engineering; Pearson Correlation Coefficient
Abstract

With the rapid development of robot technology, home robot is becoming more and more popular in daily life. Facial expression of robots is important to improve the interaction between human beings and robots. Kansei Engineering is used to explore users' feelings with the design of facial expression of home robot. Pearson Correlation Coefficient is one of the most popular similarity measures to evaluate the elements of home robot's face. In this paper we proposed a novel approach to evaluate the design of face and facial expression of home robot and help the designer improving user experience of the product.

Copyright
© 2017, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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Volume Title
Proceedings of the 7th International Conference on Education, Management, Information and Mechanical Engineering (EMIM 2017)
Series
Advances in Computer Science Research
Publication Date
April 2017
ISBN
10.2991/emim-17.2017.17
ISSN
2352-538X
DOI
10.2991/emim-17.2017.17How to use a DOI?
Copyright
© 2017, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

Cite this article

TY  - CONF
AU  - Yunyun Wei
AU  - Huanzhi Lou
PY  - 2017/04
DA  - 2017/04
TI  - A Novel Design Approach for Facial Expression of Home Robot based on Kansei Engineering
BT  - Proceedings of the 7th International Conference on Education, Management, Information and Mechanical Engineering (EMIM 2017)
PB  - Atlantis Press
SP  - 84
EP  - 88
SN  - 2352-538X
UR  - https://doi.org/10.2991/emim-17.2017.17
DO  - 10.2991/emim-17.2017.17
ID  - Wei2017/04
ER  -