Toward sociable robots

Breazeal, Cynthia

doi:10.1016/s0921-8890(02)00373-1

Cited by 726 publications

(398 citation statements)

References 9 publications

Supporting

Mentioning

378

Contrasting

Unclassified

Order By: Relevance

“…However, these ICT applications are usually computer animations displayed on PC, television screens or laptops. Moreover, people are used to interact with embodied creatures and have evolved communication skills, which both need a body for expression [3].…”

Section: Operational Goalsmentioning

confidence: 99%

“…[3], [8], [25]) that use eyes, eyelids, eyebrows and a mouth for facial expressions. The proboscis or trunk of our robot appears to be the most intriguing element according to a small survey amongst children aged 10-13.…”

Section: Attractive Trunkmentioning

confidence: 99%

“…To test the recognition of facial expression, the virtual model was used in a preliminary user-study. The study was based on a survey performed by Cynthia Breazeal evaluating the expressive behavior of Kismet [3]. We asked the subjects to compare renderings of the virtual model ( Figure 6b) with a series of line drawings of human expressions (Figure 6a).…”

Section: Recognition Testsmentioning

confidence: 99%

“…The lowest similarity was found with the surprise emotion, where slightly more children linked the surprise image with the fear sketch (29%). During the test, the observation was made (a) The sketches used in the evaluation, copied from Kismets survey, adapted from (Faigin 1990) [3].…”

Section: Recognition Testsmentioning

confidence: 99%

“…In [3], Kismet's facial expressions are generated using an interpolation based technique over a three-dimensional, componential affect space (arousal, valence, and stance). Cf.…”

Section: Emotional Interfacementioning

confidence: 99%

See 4 more Smart Citations

The Huggable Robot Probo, a Multi-disciplinary Research Platform

Goris

Saldien

Vanderniepen

et al. 2009

Communications in Computer and Information Science

View full text Add to dashboard Cite

Abstract. The concept of the huggable robot Probo is a result of the desire to improve the living conditions of children in hospital environment. These children need distraction and lots of information. In this paper we present the concept of this new robot. The robot will be employed in hospitals, as a tele-interface for entertainment, communication and medical assistance. To communicate according to social rules, the robot needs the ability to show facial expressions. Using a well defined set of Action Units (AU) it's possible to express some basic emotions. A prototype of the robot's head, capable of showing these basic emotions is presented. In order to express emotions, an emotional interface is developed. The emotions, represented as a vector in an 2D emotion space, are mapped to the DOF used in the robot. A graphical user interface to control the virtual and real prototype is also presented.

show abstract

Section: Operational Goalsmentioning

confidence: 99%

Section: Attractive Trunkmentioning

confidence: 99%

Section: Recognition Testsmentioning

confidence: 99%

Section: Recognition Testsmentioning

confidence: 99%

“…In [3], Kismet's facial expressions are generated using an interpolation based technique over a three-dimensional, componential affect space (arousal, valence, and stance). Cf.…”

Section: Emotional Interfacementioning

confidence: 99%

See 3 more Smart Citations

The Huggable Robot Probo, a Multi-disciplinary Research Platform

Goris

Saldien

Vanderniepen

et al. 2009

Communications in Computer and Information Science

View full text Add to dashboard Cite

show abstract

Social identity in trusting artificial intelligence agents: Evidence from lab and online experiments

Sun,

Xu,

2024

Manage Decis Econ

View full text Add to dashboard Cite

This paper explores human trust in artificial intelligence (AI), focusing on the effects of social categorization (ingroup vs. outgroup) and AI human‐likeness through two pre‐registered studies involving 160 participants each. The first study, a lab experiment in China, and the second, an online experiment representative of the United States, both utilized a trust game to assess trust across four conditions: ingroup‐humanoid AI, ingroup‐non‐humanoid AI, outgroup‐humanoid AI, and outgroup‐non‐humanoid AI. Results indicated higher trust for ingroup and humanoid AIs, with statistical significance. Mixed‐design ANOVA was used to analyze the data, revealing significant main effects and interactions. The second study also identified an emotional connection as a mediator in trust, suggesting significant design implications for AI in trust‐critical sectors like healthcare and autonomous transportation.

show abstract