The uncanny valley: a focus on misaligned cues

Lianne F. S. Meah; Roger K. Moore

doi:10.1007/978-3-319-11973-1_26

The uncanny valley: a focus on misaligned cues

Lianne F. S. Meah^*, Roger K. Moore

^*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceeding › Conference proceeding contribution › peer-review

23 Citations (Scopus)

Abstract

Increasingly, humanoid robots and androids are easing into society for a wide variety of different uses. Previous research has shown that careful design of such robots is crucial as subtle flaws in their appearance, vocals and movement can give rise to feelings of unease in those interacting with them. Recently, the Bayesian model for the uncanny has suggested that conflicting or misaligned cues at category boundaries may be the main attributing factor of this phenomenon. The results from this study imply that this is indeed the case and serve as empirical evidence for the Bayesian theory.

Original language	English
Title of host publication	Social robotics
Subtitle of host publication	6th International Conference, ICSR 2014 Sydney, NSW, Australia, October 27-29, 2014 proceedings
Editors	Michael Beetz, Benjamin Johnston, Mary-Anne Williams
Place of Publication	Cham
Publisher	Springer, Springer Nature
Pages	256-265
Number of pages	10
ISBN (Electronic)	9783319119731
ISBN (Print)	9783319119724
DOIs	https://doi.org/10.1007/978-3-319-11973-1_26
Publication status	Published - 2014
Externally published	Yes
Event	International Conference on Social Robotics (6th : 2014) - Sydney, Australia Duration: 27 Oct 2014 → 29 Oct 2014

Publication series

Name	Lecture Notes in Artificial Intelligence
Publisher	Springer International Publishing
Volume	8755
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Other

Other	International Conference on Social Robotics (6th : 2014)
Abbreviated title	ICSR 2014
Country/Territory	Australia
City	Sydney
Period	27/10/14 → 29/10/14

Keywords

Uncanny valley
social robotics
human-robot interaction

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10.1007/978-3-319-11973-1_26

Cite this

Meah, L. F. S., & Moore, R. K. (2014). The uncanny valley: a focus on misaligned cues. In M. Beetz, B. Johnston, & M.-A. Williams (Eds.), Social robotics: 6th International Conference, ICSR 2014 Sydney, NSW, Australia, October 27-29, 2014 proceedings (pp. 256-265). (Lecture Notes in Artificial Intelligence; Vol. 8755). Springer, Springer Nature. https://doi.org/10.1007/978-3-319-11973-1_26

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title = "The uncanny valley: a focus on misaligned cues",

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Meah, LFS & Moore, RK 2014, The uncanny valley: a focus on misaligned cues. in M Beetz, B Johnston & M-A Williams (eds), Social robotics: 6th International Conference, ICSR 2014 Sydney, NSW, Australia, October 27-29, 2014 proceedings. Lecture Notes in Artificial Intelligence, vol. 8755, Springer, Springer Nature, Cham, pp. 256-265, International Conference on Social Robotics (6th : 2014), Sydney, Australia, 27/10/14. https://doi.org/10.1007/978-3-319-11973-1_26

The uncanny valley: a focus on misaligned cues. / Meah, Lianne F. S.; Moore, Roger K.
Social robotics: 6th International Conference, ICSR 2014 Sydney, NSW, Australia, October 27-29, 2014 proceedings. ed. / Michael Beetz; Benjamin Johnston; Mary-Anne Williams. Cham: Springer, Springer Nature, 2014. p. 256-265 (Lecture Notes in Artificial Intelligence; Vol. 8755).

Research output: Chapter in Book/Report/Conference proceeding › Conference proceeding contribution › peer-review

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AB - Increasingly, humanoid robots and androids are easing into society for a wide variety of different uses. Previous research has shown that careful design of such robots is crucial as subtle flaws in their appearance, vocals and movement can give rise to feelings of unease in those interacting with them. Recently, the Bayesian model for the uncanny has suggested that conflicting or misaligned cues at category boundaries may be the main attributing factor of this phenomenon. The results from this study imply that this is indeed the case and serve as empirical evidence for the Bayesian theory.

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The uncanny valley: a focus on misaligned cues

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