robot appearance
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2022 ◽  
Vol 92 ◽  
pp. 103324
Author(s):  
Xing (Stella) Liu ◽  
Xiao (Shannon) Yi ◽  
Lisa C. Wan
Keyword(s):  

Author(s):  
Boyoung Kim ◽  
Elizabeth Phillips

Robots are entering various domains of human societies, potentially unfolding more opportunities for people to perceive robots as social agents. We expect that having robots in proximity would create unique social learning situations where humans spontaneously observe and imitate robots’ behaviors. At times, these occurrences of humans’ imitating robot behaviors may result in a spread of unsafe or unethical behaviors among humans. For responsible robot designing, therefore, we argue that it is essential to understand physical and psychological triggers of social learning in robot design. Grounded in the existing literature of social learning and the uncanny valley theories, we discuss the human-likeness of robot appearance and affective responses associated with robot appearance as likely factors that either facilitate or deter social learning. We propose practical considerations for social learning and robot design.


2021 ◽  
Author(s):  
Lichang Yao ◽  
Qi Dai ◽  
Yiyang Yu ◽  
Yuki Nishioka ◽  
Qiong Wu ◽  
...  

Author(s):  
Xinxin Sun ◽  
Wenkui Jin

AbstractRehabilitation robots are becoming an important means of assisted living for the elderly, and the appearance of rehabilitation robots directly affects the willingness of the elderly to interact with the robots. Much of the current research on robot appearance preferences relies solely on subjective evaluations, which are relatively cheap, but do not reach deep into the brain to get an accurate grasp of how humans respond to robot appearance. Using electroencephalogram signal and questionnaire survey, we studied the preference of the elderly for abstract and figurative robots. The experimental materials are derived from the pictures of 10 robots in the market. The electroencephalogram signal are collected by BrainVision Recorder and processed by BrainVision Analyzer, as well as SPSS statistical analysis. Experiment shows that the peak of figurative robot pictures is higher and the fluctuation is more intense from 350 ms to 600 ms in the central region and the right half of parietal region. While the peak of abstract robot pictures is higher and the fluctuation is more intense in the prefrontal region, and the difference between abstract robot and figurative robot is not obvious in the occipital region. Based on the electroencephalogram signal and experimental results, it provides the possibility for objective preference evaluation of the elderly to the robot designed features.


IEEE Access ◽  
2021 ◽  
pp. 1-1
Author(s):  
Emmanuel Ovalle Magallanes ◽  
Noe G. Aldana-Murillo ◽  
Juan Gabriel Avina-Cervantes ◽  
Jose Ruiz-Pinales ◽  
Jonathan Cepeda-Negrete ◽  
...  

Author(s):  
Fan Li ◽  
Danni Chang ◽  
Yisi Liu ◽  
Jian Cui ◽  
Shanshan Feng ◽  
...  

The first impression of robot appearance normally affects the interaction with physical robots. Hence, it is critically important to evaluate the humanoid robot appearance design. This study towards evaluating humanoid robot design based on global eye-tracking metrics. Two methods are selected to extract global eye-tracking metrics, including bin-analysis-based entropy and approximate entropy. The data are collected from an eye-tracking experiment, where 20 participants evaluate 12 humanoid robot appearance designs with their eye movements recorded. The humanoid robots are evaluated from five aspects, namely smartness, friendliness, pleasure, arousal, and dominance. The results show that the entropy of fixation duration and velocity, approximate entropy of saccades amplitude are positively associated with the subjective feelings induced by robot appearance. These findings can aid in better understanding the first impression of human-robot interaction and enable the eye-tracking-based evaluation of humanoid robot design. By combining the theory of design and bio-signals analysis, the study contributes to the field of Transdisciplinary Engineering.


AI & Society ◽  
2019 ◽  
Vol 35 (2) ◽  
pp. 485-500
Author(s):  
Jakub Złotowski ◽  
Ashraf Khalil ◽  
Salam Abdallah

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