Proceedings of the 27th IEEE International Symposium
on Robot and Human Interactive Communication,
Nanjing, China, August 27-31, 2018

MoBT3.1

Robot’s Impression of Appearance and Their Trustworthy
and Emotion Richness
Tetsuya Matsui1 and Seiji Yamada2
Abstract— This paper focused on the appearance of humanoid robot and their trustworthy and emotion richness
perceived. Humanoid robots that used in emotional labor isneeded to express emotion and be trusted. We experimented
with eight robots image(four mechanical face robots and foursmooth face robots) and asked the participants their impression.
We conducted explanatory factor analysis to define the factorsof robots’ impression. As a result, the factors of robots werediscovered to be different from the virtual humans’ impression.
Also, the trustworthy and emotion richness perceived of robots
depended on another factors. The familiar robots were trusted
and the human-like robots were expected to have rich emotion.

I. INTRODUCTION
Humanoid robots was already being used in the human’s
daily life. for example, as a teacher[1], a cleark[2] anda counselor[3]. These roles are called “emotional Labour”
that is needed to express and control their emotion and betrusted[4]. The effect of designing the robot’s behavior[5][6]or conversation[7][8] to construct rapport with the users
were widely researched. In this paper, we explored thefirst impression of the robots, the appearance. Goetz et al.
showed that the familiar appearance of robots prompted thelong conversation with the users[9]. Kanda et al. showedthat the difference of the robot’s appearance affected theuser’s nonverbal reactions[10]. Broadbent et al. showed thatrobots has more humanlike face was perceived to havetheir mind and personality[11]. These studied showed thatthe appearance of robots affected the user’s impression andbehavior.
In regard to the appearance of robot, the uncanny valley
theory has been discussed. The uncanny valley is the hypothesis that the user become feeling weirdness to the robots astheir appearance were being like humans[12]. The problem
is what causes this effect. Ho et al. suggested that the lackof humanness perceived caused weirdness[13]. Seyama et al.
suggested that the difference of realism of facial appearance
caused the uncanny valley[14]. MacDorman and Ishiguro
indicated that the uncanny valley was caused because somerobots reminded people death[15]. This description can beparaphrased to that the weirdness of robot was caused whenpeople felt only materiality, not agency. These explanationsuggested that the robot’s appearance give some kinds ofimpression, for example, humanness, realism, materiality andagency. Also the people fall in the uncanny valley when the
robots lose these factor’s balance.
There are another model that was suggested by Duffy[16].
He constructed triangle model to classify the robot’s head
1 Department of Computer and Information Science, Seikei university 3-3-1, Kichijojikitamachi, Musashino-shi, Tokyo, 180-8633, Japan

t-matsui@st.seikei.ac.jp
2 National Institute of Informatics and SOKENDAI 2-1-2 Hitotsubashi,
Chiyoda-ku, Tokyo, 101-8430, Japan seiji@nii.ac.jp

978-1-5386-7980-7/18/$31.00 ©2018 IEEE

design inspired by McCloud’s classification of the cartoon’s
character[17]. He defined three apexes of triangles as abstract, human and iconic. Also he suggested that the mostapposite design would achieve the balance between three
apexes[16].
In this paper, we aimed to discover the factors of impression of robots’ appearance that related to trustworthy andemotion richness perceived by users. For the robots used inreal world, trustworthy perceived by user may be importantfactor, especially, in human-robot collaboration[18]. Hancok
et al. conducted meta-analysis of trust between human androbot, and concluded that the robot’s performance is the mostimportant factor[19]. Salem et al. also reported that task
performance was important factor of robots’ trustworthy[20].
In regard to appearance, Walters et al. showed that the robot
having head were perceived more intelligent than withouthead[21]. Siegel et al. showed that male participants tended
to trust female robots[22]. However, the factors of trustworthy of humanoid robots’ appearance were not sufficiently
researched.
Also, emotion richness perceived seemed to be an important factor for the robots used for emotional labor.
Emotional contagion, the phenomenon that the someone’s
emotion affects to their partner, is important process tomake a rapport[23]. It was reported that this phenomenon
occurred between a robot and a human, used the robot’s
facial expression[24] or gesture[25]. Emotional contagion
bring some positive result, for example, to increase efficiencyof work[26] and to increase clerk’s service quality perceived
by customers[27]. In research of virtual agents, expressing
the agent’s positive emotion increase the agent’s trustworthy
perceived by human[28]. This shows that emotion richness
is important factor of designing trustworthy robots. However
it is not clear whether robots’ emotion richness perceived byhumans directly correlated the robots’ trustworthy.
To discover the factor contributed to trustworthy and emotional richness, we used two dimensional mind perception
model. This model was suggested by Gray et al.[29]. In thispaper, Gray et al. suggested two factors of mind perception,agency and experience. This model was used in field of HRI.
Gray and Wegner showed that people felt weirdness to robots
when the robots has only agency without experience[30].
This model was constructed by many types of agent, human,
animal, god and robot. This model may valid to measure thedifference of impression between animal and robot, or humanoid robot and non-humanoid robot. However, we focusedon the variation of mind perception among humanoid robot.
Thus we planned to use not only agency-experience model,
but also familiarity-reality model. This model was suggested
by Matsui and Yamada[31] to measure the difference ofimpression among humanoid virtual agent. We aimed to88verify the relationship between the robot’s trustworthy or
emotion richness and these four factors, agency, experience,familiarity and reality.
We especially focused on the robots’ face. We defined
the two types of robots’ face, the mechanical face andsmooth face. Mechanical face means the face that exposed
small metal plates and inner structures, or forms geometricaloutlines with big eyes. Smooth face means the face that havehuman like skin or soft surface substances and smooth outlines. It was reported that robot’s face affected on the users’
perception. Yamashita et al. showed that the robot having
mechanical face and the robot having humanoid face gave thedifferent impressions and touch sensation[32]. Kalegina et al.
showed that robots’ facial appearance(eyes, mouth and skincolors) affected their perceived trustworthy[33]. Phillips et al.
showed that robots’ eyelashes, eyebrows and skin contributed
the main factor of the robots’ appearance[34]. MacDorman
conducted an experience with images morphing from humanto robot and showed that people felt more familiarity tohuman face than robot face and an intermediate face[35].
From these prior works, we hypothesized that the robots withsmooth face are more trusted by participants than the robots
with mechanical face.
In this paper, we aimed to verify the following hypothesis.
• H1: There are factors of the robots’ impression perceived that correlating with the robot’s trustworthy andemotion richness perceived• H2: The robots with a smooth face will be more trusted
by participants than the robots with mechanical face
• H3: There are high correlations between the robots’trustworthy and emotion richness perceived
We aimed to define the factor and verify these hypothesis.
II. EXPERIMENT
We recruited all participants on Yahoo Crowd Sourcing1 ,the web site. All participants received a reward of 30 yen(about 28 US cents). We recruited 92 Japanese participants,
and 87 remained after noise exclusion. There were 51 males
and 36 females, and they were aged between 19 and 67, foran average of 40.4(SD = 9.3).
We used eight robots images(photo or illustration). All
images are under Creative Commons licenses. All images
are shown in Table I2 . Four robots have mechanical face(a,1 https://crowdsourcing.yahoo.co.jp/
2 a:”S.H Horikawa Star Strider Robot Front.jpg”, by D J Shin,

https://www.flickr.com/photos/51940189@N04
b:”Buckley Robotics Class”, by Kathrine McDowell,
http://www.buckley.af.mil/News/Photos/igphoto/2000361362/
c:”Kojiro Robot.jpg”, by Erico Guizzo,
http://spectrum.ieee.org/automaton/robotics/humanoids/kojiromusculoskeletal-humanoid-robotd:”SARCOS Primus humanoid robot”, by Jiuguang Wang,
https://i.pinimg.com/736x/d3/21/8c/d3218c17856dc0be47905e174c7c4495–
real-robots-humanoid-robot.jpg
e:The work of TheDigitalArtist, by TheDigitalArtist,
https://cdn.pixabay.com/photo/2016/07/30/13/05/robot1557085 960 720.png
f:”Sony Qrio Robot.jpg”, by Dschen Reinecke,
https://en.wikipedia.org/wiki/Portal:Robotics/Featured robot
g:”Sophia (robot) 2.jpg”, by International Telecommunication Union,
https://en.wikipedia.org/wiki/Sophia (robot)h:”Sanbot King Kong.jpg”, by QIHAN Technology,
https://en.wikipedia.org/wiki/Sanbot (robot)

978-1-5386-7980-7/18/$31.00 ©2018 IEEEb, c, d) and other four robots have smooth skinned face(e, f,g, h).
We asked the participants to answer two sets of questions
to construct two-dimensional mind perception models. One
set of questions was cited from Gray et al.[36] to construct
an agency-experience model. This set was constructed asfollows.
Fear: How capable of feeling fear do you think thisrobot is?
• Pleasure: How capable of feeling pleasure do you think
this robot is?
• Hunger: How capable of feeling hunger do you think
this robot is?
• Self control: How capable of feeling self control do you
think this robot is?
• Memory: How capable of remembering do you think
this robot is?
• Moral: How capable of acting morally do you think thisrobot is?
•The first three questions are related to the agency factor,
and the latter three are related to the experience factor[36].
The other set of questions was constructed by Matsui and
Yamada [31]. The questions were constructed to derive two
factors, reality and familiarity. This set was constructed asfollows.
Familiarity: How capable of feeling familiarity do you
think this robot is?
• Warmth: How capable of feeling warmth do you think
this robot is?
• Communication: How capable of feeling communication possibilities do you think this robot is?
• Alive: How capable of feeling aliveness do you think
this robot is?
• Human-likeness: How capable of feeling humanlikeness do you think this robot is?
• Reality: How capable of feeling reality do you think
this robot is?
•

The first three questions are related to the familiarity
factor, and the latter three are related to the reality factor[31].
We conducted an explanatory factor analysis (EFA) todefine two factors and constructed two-dimensional mind
perception models. EFA is a statistical method that is widelyused to define hidden factors [37]. We conducted the EFA
with principal axis factoring method and varimax rotationand set the number of factors to two because our aim wasto construct two-dimensional models.
Also, we asked one more question to measure the trustworthy perceived and emotion richness perceived of eachrobots.
••Trust: Do you feel how trustworthy is this robot?
Emotion richness: Do you feel how rich is this robot’s
emotion?

We defined the average of this question as the trust leveland emotion richness level. The participants answered allquestions on a 7-point Likert scale.

89

TABLE II
FACTOR LOADING OF “AGENCY ”-“ EXPERIENCE ” QUESTIONS
question
pleasurefear
moral
hungermemoryself control
contribution rate
Cronbach’s αafactor 1
.893
.854
.814
.776
.445
.672
.574
.986

factor 2
.425
.501
.571
.605
.893
.728
.408
.959

b

III. RESULT
A. Agency and experience model
Table II shows the factor loadings of the agencyexperience questions and the contribution rate and Cronbach’s α of each factors. This result didn’t completely
match agency-experience model. In Gray’s model[36] , fear,
pleasure and hunger contribute agency. However in our
result, fear, pleasure, hunger and moral contributed factor
1. Also, Self control and memory contributed factor 2. We
defined factor 1 as modified agency and factor 2 as modified
experience, because of the difference between these factors
and original agency and experience. The both of Cronbach’s
α are higher than 0.9, thus these factors have high degreeof internal consistency. However, in this result, only twovariables contributed to factor 2. In general, one factor needs
at least three variables[38]. Thus, this result didn’t havea high degree of confidence. We employed only modified
agency factors in the following analysis.

cdB. Familiarity and reality modele

Table III shows the factor loadings of the familiarityreality questions and the contribution rate and Cronbach’s α of each factor. This result didn’t completely
match familiarity-reality model suggested by Matsui and
Yamada[31]. In this model, human-likeness, alive and reality
contribute “reality” and familiarity, warmth and communication contributed “familiarity”. However in this result,human-likeness, alive and communication contributed factor
1 and familiarity, warmth and reality contributed factor 2. We
defined factor 1 as modified reality and factor 2 as modified
familiarity, because of the difference between these factors
with original reality and familiarity. The both of Cronbach’s
α are higher than 0.8, thus these factors have high degree ofinternal consistency.
Figure 1 shows each factor scores of robots. Each plotmeans each robot.

fg

C. Trust level, emotion richness level and each factor scoreh

TABLE IROBOTS USED IN EXPERIMENT

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Figure 2 shows the average of trust score of each robot.
Error bar means standard deviation. We conducted ANOVA
and there was significant difference(F(7, 688) = 5.07, p< .001). We conducted multiple comparison with Tukey’s
method, there were significant differences between a and e,a and f, d and f, and f and g(p < .005).
We conducted t-test between mechanical face robot
and smooth face robot, and there were a significant
difference(t(347) = -3.751, p < .001).

90TABLE III
FACTOR LOADING OF “ FAMILIARITY ” AND “ REALITY ”
QUESTIONNAIRES

Questionnaires
human-likeness
alive
communication
familiarity
warmthrealitycontribution rate
Cronbach’s α

factor 1
.978
.974
.921
.032
.106
.345
.481
.934

factor 2
-.051
.214
.368
.979
.925
.778
.434
.881

Fig. 2.

The average of trust level
TABLE IV

CORRELATION COEFFICIENTS BETWEEN EACH FACTOR SCORES OF EACHROBOTS AND TRUST LEVEL

Fig. 1.

Factor scores for each robot

Table IV shows the correlation coefficients between factor
scores and average of each questionnaire of each robots andtrust level.
Figure 3 shows the average of emotion richness scoreof each robot. Error bar means standard deviation. We
conducted ANOVA and there was significant difference(F(7,688) = 14.91, p < .001). We conducted multiple comparison with Tukey’s method, there were significant differences
between a and b, a and c, a and e, a and f, a and h, b and d,b and g, c and d, a and e, c and g, d and f, d and h, e andg, f and g, and g and h(p < .005).
We conducted t-test between mechanical face robot
and smooth face robot, and there were no significant
difference(t(347) = -0.940, p > .1).
Table V shows the correlation coefficients between factor
scores average of each questionnaire of each robots and trustlevel. Also we calculated the correlation coefficient between
trust level and emotion richness level(r = .0.706).
IV. DISCUSSION
A. Explanatory factor analysis
Table II shows the EFA didn’t reveal two establishedfactors, agency and experience. This result conflicted withprior works. This result may be derived from that weused only humanoid robots. Agency and experience model
was ordinary constructed by research with many kind of
agents(human, animal, robots and so on)[29]. These agentshad various appearances and textured. Especially, whether
the robots have face or not is important factors in users’
perception[21]. In this research, all robots had fundamentally
similar appearance and all of them had their face. This

978-1-5386-7980-7/18/$31.00 ©2018 IEEE

score
modified agency
modified reality
modified familiarity
pleasurefear
moral
hungermemoryself control
human-likeness
alive
communication
familiarity
warmthrealitycorrelation coefficients
.458
.530
.783
.670
.536
.695
.554
.608
.707
.426
.687
.815
.800
.694
.850

seemed to be reason that we couldn’t reproduce agency andexperience model. This is one of new insights in this paper.
Also, Table III shows the EFA didn’t reveal reality andfamiliarity factors. These factors were derived by research
about virtual humans[31]. Thus we have concluded that
this conflict occurred by difference between robots andvirtual agents. Regarding robots, “How capable of feelingreality do you think this agent is” is the obvious question
because the robots existed in real world. Also Li showedthat robots or embodied agents were more effective thanvirtual agents[39]. This result is suitable to the result thatfamiliarity, warmth and reality contributed the same factor.
This factor is modified familiarity, the familiarity of therobots. Alternatively, whether the robot can communicate
with the user is important problem when we interact withrobots. Prior work showed the smooth utterances made theparticipants feel the robots’ mind[40] Also robots has morehuman-like face was perceived to have their mind[11]. These
works suggest that people feel mind of robot when they cancommunicate smoothly or were looked like human, and having mind is almost the same as being alive. This seemed to bereason to why aliveness, human likeness and communication
contributed the same factor. This factor means how capableof reacting as human the participants feel the robot is. Thisis modified reality, the reality of robots. This results show
the new findings of robot’s appearance. For people, “How91

Fig. 3.

The average of emotion richness level
TABLE V

CORRELATION COEFFICIENTS BETWEEN EACH FACTOR SCORES OF EACHROBOTS AND EMOTION RICHNESS LEVEL

factormodified agency
modified reality
modified familiarity
pleasurefear
moral
hungermemoryself control
human-likeness
alive
communication
familiarity
warmthrealitycorrelation coefficient
.912
.925
.330
.987
.935
.968
.913
.733
.884
.912
.976
.958
.345
.461
.525

capable of feeling familiarity do you think this robot is?” and“How capable of feeling communication possibilities do you
think this agent is” are another problem. Our result showedthat the factor of perception of humanoid robots was different
from virtual agents or other agents because of their face andembodiment.
Figure 1 shows the factor score of modified reality andmodified familiarity. From this figure, we can know thetrends of relationship between the robots’ face and eachfactor. In mechanical face robots, there are no deviations.
This results shows that mechanical face it self has little
affect to perceptions. In smooth face robots, three of thefour robots have positive values of modified familiarity. In
this experiment, the smooth face brought the perceptionof familiarity and warmth, however didn’t bring communication possibilities. Alternatively, no.g, android robot thathas human-like facial skin has lower score of modified
reality. This result seemed to be caused from uncanny
valley effect. It is reported that immoderate human-likenessof appearance reminded people dead body[15]. Also, thisexperiment was conducted with only images, without movies
and interactions. This may cause the more high effect ofreminding death. This result is different from research ofvirtual agents[31]. This may be caused the appropriate aspectof robots, especially the embodiment.
B. Trust level and emotion richness level
Figure 2 shows that the robots have smooth face havehigher trustworthy than the robots have mechanical face.
This result supported our hypothesis 2. Also Table IV showsthat modified familiarity factor and trust level are found to978-1-5386-7980-7/18/$31.00 ©2018 IEEE

have a high correlation. This result supported our hypothesis
1. This result suggests that the robots’ familiarity have aconnection with expected performance. Prior woks pointed
out that the robots’ performance was important factor of therobots’ trustworthy[19][20]. However, this result suggested
that “How capable of feeling familiarity do you think thisrobot is?” is more important problem than “How capable offeeling human-likeness do you think this agent is?” when we
judged only from the robots’ appearance.
Figure 3 shows that we couldn’t find the relationshipbetween the robots’ facial smoothness and emotion richness. There are possibility that the robots’ emotion richness is affected from fineness of face, regardless of theirmachinelikeness or smoothness. Also Table V shows thatdifferent tendency of perceived emotion richness from perceived trustworthy. This table shows that modified agency
factor and modified reality factor have high correlation
with emotion richness level. This result suggests that the
robots’ emotional contagion effect is affected by their reality,
not familiarity. When we consider the interaction with therobots, emotional expression may increase their trustworthy
as virtual agents[28]. However, regarding first impression
by sight, people suppose the robots’ trustworthy by their
human likeness and aliveness. Also there are relatively little
correlation between trustworthy and emotion richness. This
result conflict with our hypothesis 3. This result suggested
that people use two method to suppose the robots’ trustworthy. When they have enough time to interact with robots,
they judged the robots’ trustworthy by familiarity perceived.
Although when they are forced to be judged trustworthy ata glance, they judged trustworthy by reality perceived.
V. CONCLUSIONSIn this paper, we aimed to defined factors of the robots’appearance impression and verify the correlations between
these factors and the robots’ trustworthy and emotion richness perceived by human. We used eight robots images thathave mechanical face or smooth face. We asked the Japaneseparticipants two sets of questionnaires to define factors. As
a result, we concluded the robots have different factors
from other agents and virtual agents. As robots, familiarity
and reality contributed the same factor. Also aliveness andcommunication communication possibilities contributed thesame factor. Also we measured the robots’ trustworthy andemotion richness perceived. We concluded that the robots
having smooth face were more trusted than robots having
mechanical face and trustworthy was correlated with familiarity and emotion richness was correlated with reality. These
result conclude that people perceive the robots’ trustworthy
and emotion richness from different factors and suggest theeffective way to design the robots’ appearance.
ACKNOWLEDGEMENTS
This research was partially supported by JSPS KAKENHI“Cognitive Interaction Design” (No. 26118005).
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