This is the author's version of an article that has been published in this journal. Changes were made to this version by the publisher prior to publication.
The final version of record is available at
http://dx.doi.org/10.1109/LRA.2018.2856303

IEEE ROBOTICS AND AUTOMATION LETTERS. PREPRINT VERSION. ACCEPTED JUNE, 20181

How should a Robot React before People’s
Touch?: Modeling a Pre-Touch Reaction
Distance for a Robot’s Face
Masahiro Shiomi1, Kodai Shatani1,2, Takashi Minato1, and Hiroshi Ishiguro1

Abstract— This study addresses the pre-touch reaction
distance effects in human-robot touch interaction with an android
named ERICA that has a feminine, human-like appearance. Past
studies on human-robot interaction, which enabled social robots
to react to being touched by developing several sensing systems
and designing reaction behaviors, focused on after-touch
situations, i.e., before-touch situations received less attention. In
this study, we conducted a data collection to investigate theminimum comfortable distance to another’s touch by observing adataset of human-human touch interactions, modeled its distance
relationships, and implemented a model with our robot. We
experimentally investigated the effectiveness of the modeled
minimum comfortable distance to being touched withparticipants. Our experiment results showed that they highly
evaluated a robot that reacts to being touched based on themodeled minimum comfortable distance.
Index Terms—Human-robot interaction, Human factors

T

I. INTRODUCTION

HE physical existence of social robots enables us tointeract with them through haptic interactions. Human
science literature has broadly reported haptic interaction andpositive effects in both physical and mental perspectives [1-6].
Following these results, robotics researchers also reported
similar positive effects of haptic interaction with robots, e.g.,
mental therapy effects of a seal robot for elderly care [7], stressbuffering effects [8], motivation improvements formonotonous tasks [9], encouraging prosocial behaviors [10][11], encouraging self-disclosure behaviors, and motivations tointeract with a robot [12, 13]. In addition, robotics researchersinvestigated what kinds of behaviors are essential for natural
reactions to being touched by interaction partners [14, 15].
These studies identified the potential of haptic interaction
with social robots and provided essential knowledge for haptic
interaction design. However, they focused on the behaviors or
Manuscript received: February 22, 2018; Revised: May 23, 2018; Accepted:
June 18, 2018.
This paper was recommended for publication by Dongheui Lee uponevaluation of the Associate Editor and Reviewers’ comments.
This work was supported by the JST ERATO Ishiguro Symbiotic Human
Robot Interaction Project (Grant Number: JPMJER1401), and JSPS
KAKENHI Grant Numbers JP16K12505 and JP17K00293.
1
M. Shiomi, K. Shatani, T. Minato, and H. Ishiguro are with ATR, Kyoto,
Japan. (e-mail: m-shiomi@atr.jp)
2
K. Shatani and H. Ishiguro are also with Osaka Univ., Osaka, Japan.
Digital Object Identifier (DOI): see top of this page.

the effects of haptic interaction “after” being touched; lessfocus has been directed at how to deal with a robot’s pre-touch
behaviors. How should robots behave before they are touched?
Perhaps they should react at a certain distance to another's hand
like humans do for more natural interactions. Unfortunately,
the effects of such pre-touch reactions remain uninvestigated aswell as what reaction distance is actually deemed appropriate.
In human science literature, people choose certain distancesfrom others in conversation situations. Such knowledge wassummarized as proxemics by E.T. Hall [16], and many social
robots employ its knowledge to interact with people for morenatural distance relationships [17-30]. Inspired by Hall’s study
on proxemics, the ultimate goal of our study is to gather
knowledge about it in touch interactions, particularly “before”
being touched situations. We defined the specified proxemics
in before-being-touched situations as pre-touch proxemics,
which will provide knowledge for robots to achieve natural
behaviors or reactions for touch interactions with people.
As a first step for this goal, we investigate the minimum
comfortable distance between a face and a hand in touch
interactions, because such knowledge will be the foundation
for touch reactions for social robots in haptic interactions. We
conducted a data collection with human participants who
moved their hands toward the faces of others and measured theminimum comfortable distance between their faces and thehands to identify the permissible boundaries around the face.
Next we analyzed these collected data and implemented theboundary information in ERICA (Fig.1), our social robot, [31].
Finally we experimentally investigated whether our model can
provide natural impressions to people who moved their hands
toward it. Thus, this study answers the following twoquestions:- What is the minimum comfortable distance inhuman-human touch interaction around the face?
- Should a robot react before being touched by a person? If
so, should its reaction obey the minimum comfortable distanceof people?

Fig. 1. ERICA reacts before being touched.

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This is the author's version of an article that has been published in this journal. Changes were made to this version by the publisher prior to publication.
The final version of record is available at
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2IEEE ROBOTICS AND AUTOMATION LETTERS. PREPRINT VERSION. ACCEPTED JUNE, 2018
II. RELATED WORK

A. Human-Robot Touch Interaction
In touch interactions with people, sensing capabilities are
essential for social robots. Several researchers have developed
sensing mechanisms and/or algorithms for such robots [32-34].
Due to an increase of sensing capabilities in touch interactions,robotics researchers have started to investigate the positiveeffects on people of haptic interaction with social robots [35,36]. For instance, Paro, a touchable seal robot, is a pet-typesocial robot for the mental health support of the elderly [7].
Researchers have also addressed the effects ofverbal/non-verbal cues during haptic interactions. For theeffects of the latter, Hirano et al. investigated how gazebehaviors and touch styles changed the impressions of touch
interactions [37]. Chen et al. investigated the effects of verbal
cues in a nursing context and studied how the timing and thecontents of verbal cues change the impressions of being
touched [14]. From another perspective, researchers focused ondance situations where both verbal/non-verbal cues are
essential for collaboration between robots and people [38-40].
These research works identified the effectiveness of touch
interaction with social robots and provided appropriate design
policies for haptic interactions. However, these studies mainly
dealt with after-touch situations and focused less on
before-touch (potential/imminent touch) situations. In thisstudy, we conducted a data collection between humans toconstruct per-touch proxemics knowledge and implemented itin our robot to investigate its effectiveness and validity forhuman-robot touch interactions in before-touch situations.
B. Proxemics in Human-Robot Interaction
Proxemics is one common theory about the use of space forhumans in social situations [16]. Researchers often refer to thisknowledge when developing social robots that interact withpeople to adjust the distance based on their relationships:socially-aware navigation [17, 18], path planning [19] [20],approaching, [21], and showing friendliness [22]. From
another perspective, researchers investigated which features
influence the minimum comfortable distance between people
and robots: the personality of the people [23-25], the robot size[26], and verbal information and body postures [27, 28]. In
addition, other researchers assumed that distances can be used
to estimate the personality of the interacting partners throughinteraction activity with social robots [29, 30].
Several researchers have modeled such personal spaces
around people. For example, Amaoka et al. defined personal
space as two Gaussians with more space in the front [41].
Svenstrup et al. identified a personal space that is larger behind
the individual [42]. Related to the above previous work, both ofthese studies enabled social robots to interact with people
considering appropriate distance relationships based on theinteracting situations.
On the other hand, proxemics is less focused on haptic
interaction situations because its knowledge is mainly derived
from analyzing conversational situations [16]; the minimum
comfortable distance relationship reflects the body parts of theinteracting people. In other words, it remains unknown how

robots should react when they are touched. In this study, we
focused on haptic interactions and the minimum comfortabledistance relationship between the touched body part (i.e., theface) and the part doing the touching (i.e., the hand) inclose-distance relationships, which is the main difference
between proxemics and pre-touch proxemics.
III. ANALYZING MINIMUM COMFORTABLE DISTANCE
To investigate the minimum comfortable distance fortouching in human-human interaction, we conducted a datacollection with human participants.
A. Data Collection
1) Overview
In this data collection, we gathered distance data between thehand of a person who is going to touch (toucher) and the face ofa person about to be touched (evaluator). As a first step forknowledge about pre-touch proxemics, we focused on the
distance around the face to investigate the relationship between
the evaluator's gaze direction and the toucher's touch angle toidentify a minimum comfortable distance. If the gaze direction
strongly influences this distance, such knowledge will be
useful for investigating and designing the minimum
comfortable distance for other body parts.
We gathered data from both female and maletouchers/evaluators, because past studies reported that thegender of the interacting partners influences the minimum
comfortable distances of the proxemics perspective [43-45].
We expect similar effects will occur in touch situations.
2) Procedure
We followed the similar approaches of past proxemics
studies that investigated the minimum comfortable distance
between people and robots [23-28]. For example, many studies
fixed the evaluators’ positions including the face direction, andthen others or robots slowly approached the evaluators. Whenthey felt discomfort based on the encroaching of others, theyexpressed it, and the distance of the discomfort was recorded as
the minimum comfortable distance. By following theseprocedures, the touchers slowly stretched out their hands
toward the evaluators’ face and freely decided their initial hand
positions to cover various angles. When the evaluators wanted
the hand’s approach to stop, they clicked a mouse and theseclicking sounds were audible to the touchers. When they heard
the clicks, they were instructed to immediately stop moving
their hands. Thus, we measured the minimum comfortabledistance between their faces and the hands of the touchers.
Figure 2 shows the environment of the data collection. A
pair of one toucher and one evaluator enter the room, and thenthe evaluators sat on a chair in the middle of the room. The
experimenter asked them to look at a mark on the front of thechair to maintain their gaze direction. The touchers stoodaround the evaluators at a distance of 1.0 m (adjusted based on
the arm’s length of the touchers). The nine candidates of thestanding positions are shown as 0 to 8 (Fig. 2, left). We asked
the participants to continue the data collection as much as
possible within the time, not decided the number of touching.

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This is the author's version of an article that has been published in this journal. Changes were made to this version by the publisher prior to publication.
The final version of record is available at
http://dx.doi.org/10.1109/LRA.2018.2856303

SHIOMI et al.: PRE-TOUCH REACTION DISTANCE FOR ROBOT’S FACE

Kinect

８

E

０

2.0 m

T

４

Fig. 2. Data collection environment: Toucher stands at “6” and stretches her
hand toward evaluator.

Fig. 3. Distance definitions in our date collection.

3) Recording data
To automatically track the respective positions of the hands
and the faces of the touchers and the evaluators, we used two
Kinect V2 sensors mounted behind the latter. Kinect’s libraryprovides highly stable and reliable 3D positions of each joint of
the toucher, including the center of the hands (Phand in Fig. 3)
and the 3D head positions of the evaluators (Pface in Fig. 3). We
recorded all the position data from the Kinect V2 sensors andthe timing of the mouse clicks by the evaluator. To calculate
the minimum comfortable distance between a toucher’s handand an evaluator’s face (Dmc in Fig. 3), we subtracted the size of
their hands (Dhand in Fig. 3, directly measured beforehand) andthe average Japanese face size (Dface in Fig. 3, 9 cm for females
and 10 cm for males, based a previous work [46]).
We used a multiple Kinect V2 for our joint position tracking
system because we wanted a marker-less joint tracking system.
We were concerned that attaching markers to the evaluators’
faces and the touchers’ hands would influence the minimum
comfort distance because their physical existence might change
the before-touch feelings. Even though a past study argued that
this sensor is suitable for applications that requirejoint-position accuracy that does not exceed a couple ofcentimeters [47], it focused on the accuracy of a whole bodytracking algorithm for upper limbs in a rehabilitation process,which is quite different from our study that is focusing on thepositions of the touchers’ hands and the evaluators’ faces. For
the above reasons, we chose multiple Kinect V2 sensors. To
increase the accuracy of the recognized joint positions, wecalibrated the relative positions of multiple sensors and usedtheir absolute positions to integrate their joint position data. If
one Kinect sensor failed to estimate the joint positions, we used
the other Kinect data if the estimated data were continuous andstable.

3

B. Analysis
In our data collection, 40 pairs of participants (10 pairs arefemale touchers and female evaluators, 10 pairs are female
touchers and male evaluators, 10 pairs are male touchers andfemale evaluator, and 10 pairs are male touchers and maleevaluators) participated in the cumulative total. Their averageages and SDs were 21.825 and 1.53, respectively. The total
number of distance data was 11699 (average per toucher andSD were 292.5 and 81.1). Due to the personal differences in theminimum comfortable distance, the touch speed, thepreparation time for data collection, occlusions due to the bodysizes of the participants, the number of data for each participant
was different. So we averaged the minimum comfortabledistances for each evaluator and used them for analysis.
Based on these data, first, we investigated the averageminimum comfortable distance of all the participants; thevalues and their SD were 19.97 cm and 8.484. We analyzed
these data based on the following four viewpoints to scrutinize
what factors influence minimum comfortable distance:
1) Gender
Since past studies reported that females preferred shorter
personal distances than males [43, 44], we expected gender toinfluence the minimum comfortable distance (Table I).
Therefore, we conducted a two-factor ANOVA with minimum
comfortable distance as a dependent variable, the toucher’s
gender, and the evaluator’s gender. There were no significant
differences in the toucher’s gender (F(1, 39)=.012, p=.914, η2= .001), the evaluator’s gender (F(1, 39)=.020, p=.888, η2= .001), or in their interaction (F(1, 39)=3.844, p=.058, η2= .096). The additional data collection suggests that theminimum comfortable distance increases with the opposite
gender, but it did not show a significant effect. For reference,
multiple comparisons with the Bonferroni method forinteraction effects did not show any significant
differences/trends. Thus, at least in this data collection, thegender of the touchers did not significantly affect the minimum
comfortable distance.
2) Angle
Next we investigated the angle effects of the minimum
comfortable distance because we thought that the touchdirection might influence it (Table II). We used the averageminimum comfortable distance by combining both genders inthis analysis because gender did not show any significant
differences in the above analysis. First, we conducted a paired
t-test that compared the minimum comfortable distances when
the touchers’ hands approached from the right (M=19.738,
SD=8.96) or the left (M=19.811, SD=8.80) and found no
significant differences (t(39)=0.188, p=.851, d=.003). Next we
conducted a paired t-test that compared the minimum
comfortable distances when the touchers’ hands approachedfrom above (M=18.438, SD=8.54) or below compared to theheights of the evaluators eyes (M=19.442, SD=11.38) andidentified no significant difference (t(39)=1.135, p=.263,
d=.018). Note that “right” means that the angle between theevaluator’s face and the toucher’s hand is on “stage right” fromthe front of the evaluator’s face when the evaluator clicked the
button.

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Thus, neither right/left nor upper/lower angles between thetouchers’ hands and evaluators’ faces significantly affected theminimum comfortable distance.
3) Speed
Next we investigated how the speed of the touchers’ hands
influenced the data collection. Even though we asked theparticipants to move their hands slowly, they performed theaction at slightly different speeds, which might have affected
the minimum comfortable distance. We investigated therelationship between the speed of their hands and the minimum
comfortable distance and found a weak positive correlation(r=0.197, p<.001). Of course, if their hands are approaching
faster, evaluators might feel more anxious and respond quickly,
but in our settings the speeds within the touching situation only
showed a weak positive correlation with the minimum
comfortable distance.
4) Acclimation
Finally, we investigated whether the evaluators’ minimum
comfortable distances changed as time progressed (Table II). In
this data collection, since the evaluators experienced many
touching interactions, their perceptions might have been
influenced. We conducted a paired t-test that compared theminimum comfortable distances between the averages of thefirst 10 (M=21.283, SD=9.00) and the last 10 bits of data
(M=19.324, SD=9.62), and found a significant trend(t(39)=1.804, p=.079, d=.028), but the difference was less than
2 cm. Thus, in this data collection, acclimation due to a large
number of touching interactions did not significantly affect theminimum comfortable distance.

C. Summary
Based on the above analysis, several factors, such as genderand the right-left and upper/lower angles, did not show
significant differences in the minimum comfortable distances.
The acclimation effects showed a significant trend but thedifference was less than 2 cm. Therefore, we used the averageminimum comfortable distance of all the gathered data by
combining the genders, the hands, and the angles: 20 cm as areaction distance. Fig. 4 shows an example of the distributionsof the minimum comfortable distances from an evaluator; thedata are distributed around 20 cm from the face, regardless of
the angles.

Fig. 5 Clustering results by depth data from a Kinect V2 sensor

Fig. 6 Reaction to being touched in touch condition
TABLE I.

AVERAGE AND SD OF MINIMUM COMFORTABLE DISTANCE BY
GENDER

Toucher

Evaluator

GenderMale

FemaleMale17.609 (7.638)

22.729 (8.913)

Female22.639 (10.844)

16.914 (7.112)

TABLE II.

AVERAGE AND SD OF MINIMUM COMFORTABLE DISTANCES BYCONSIDERING ANGLE AND ACCLIMATION (P-VALUES CORRESPOND TOPREVIOUSLY COMPUTED T-TESTS)

Angle

Acclimation

Right

Left

p-value

19.738 (8.96)

19.811 (8.80)

0.851

Upper

Lower

p-value

18.435 (8.54)

19.442 (11.38)

0.263

First ten times

Last ten times

p-value

21.283 (9.00)

19.324 (9.62)

0.079

Fig. 4. Toucher’s hand positions when an evaluator clicked button to stop
the handFig. 7 Reaction to a potential touch in intimate-distance condition

E

KinectT
1

Fig. 8 Experiment environment and touching angles

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This is the author's version of an article that has been published in this journal. Changes were made to this version by the publisher prior to publication.
The final version of record is available at
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SHIOMI et al.: PRE-TOUCH REACTION DISTANCE FOR ROBOT’S FACE
IV. EXPERIMENT
A. Hypothesis and Predictions
Past studies revealed the effectiveness of human-robot touch
interaction and achieved appropriate reactive behaviors for
robots after their touches. However, the reaction behaviors of
the pre-touch situations received less focus; e.g., the robots inpast studies generally reacted after being touched, not before.
From a proxemics perspective, the intimate distance for close
people was 45 cm, which can be used for touch interactions, butthese definitions were defined based on the analysis ofconversational situations, not pre-touch situations. Therefore,
the appropriate pre-touch reaction distance remains unknown.
To identify an appropriate reaction distance, we developed amodel of minimum comfort based on the observations of the
pre-touch reactions of people. Regardless of the gender
relationships between touchers and evaluators, the averageminimum comfortable distance was 20 cm. If our modeling isappropriate, the robot should be perceived as more humanlike,more natural, and create more positive impressions than a robotthat reacts after being touched or reacts at an intimate distanceto a potential touch. We made the following three predictions:
Prediction 1: If the robot reacts at 20 cm to a potential touch,its reaction distance will be perceived as more humanlike than arobot that reacts after being touched or at 45 cm.
Prediction 2: If the robot reacts at 20 cm to a potential touch,its reaction distance will be perceived as more natural than arobot that reacts after being touched or at 45 cm.
Prediction 3: If the robot reacts at 20 cm to a potential touch,people will more positively evaluate it than one that reacts after
being touched or at 45 cm.
B. Robot System
To verify our predictions, we used ERICA, an intelligent,conversational android characterized by its human-likeappearance [31], and a Kinect V2 sensor to detect the positionsof the nearest object to ERICA’s face. We also employed a
PCL library [48] to make a clustering 3D object and FLANN[49] to measure the reaction distance (Fig. 5, right, Dreaction).
The average calculation frequency was less than 100 msec inour settings.
C. Conditions
Our experiment had a within participant design. Eachparticipant joined the three conditions described below. Theirorder was counterbalanced. In each condition, when the
distance (Dreaction) was lower than the threshold values, therobot immediately looked at the participant’s face.
Even though we found a significant difference between
approaches from above or below, it was only 3 cm. Thisdifference is significant, but its size is small. Rather thanfocusing on only a few cm of difference about the minimum
comfortable distance, we compared different thresholds.
Touch: In this condition, the robot reacts to being touched bya participant after she/he actually touched the robot’s nose (Fig.
6). Dreaction is 0 cm. Since this condition is only
semi-autonomous, to accurately react to the timing of being
touched, the operator controlled the robot’s reaction behavior.

5

Proposed: In this condition, the robot reacts to a potential
touch from a participant when Dreaction is less than 20 cm (Fig.
1). The robot is fully autonomous in this condition.
Intimate-distance: In this condition, the robot reacts to apotential touch when Dreaction is less than 45 cm (Fig. 7). The
robot is fully autonomous in this condition, too.
D. Participants
Thirty people participated: 15 women and 15 men whose
average ages were 23.0, SD 2.58.
E. Procedure
Before the experiment, the participants were given a brief
description of its purpose and procedure. This research wasapproved by our institution’s ethics committee for studies
involving human participants. Written, informed consent was
obtained from all of them.
First, we explained to the participants that the robot willreact to being touched by them based on the robot’s minimum
discomfort distance. We asked them to slowly move their hand
as if to touch the robot’s face until it reacts to the potential
touch. We explained that our experiment has three conditions,and in each one we asked the participants to approach therobot’s face from three different standing positions (0, 1 and 2,
left-top of Fig. 8) and three different angles (above, front, andbelow, Fig. 8) by both hands. In each condition the participants
did the 3 positions x 3 angles x 2 hands = 18 hand approaches toexperience sufficient pre-touch interactions. As they reached
out with their arms to touch, we asked them to maintain a slow
and constant speed to avoid speed effects. The order of eachcondition was counterbalanced, and after each condition they
filled out questionnaires about their feelings to the robot’s
reactions.
F. Measurements
To investigate their feelings based on the different reaction
distances of the robot to the participants, we measured withquestionnaires three subjective items on a 1-to-7 point scale (7is most positive): the feeling of humanlike-ness about thereaction distance (“I think that the robot’s reaction distance ishuman-like”), the naturalness of the reaction distance (“I thinkthat the robot’s reaction distance is natural”), and their overall
feelings about the robot (“I have a good impression of the robot
overall”).
V. RESULTS
A. Verification of Prediction 1
Figure 9 shows the questionnaire results about thehumanlike-ness of the reaction distance. We conducted a
two-factor mixed ANOVA for the gender and distance factors,
and the results showed significant differences in the distancefactor (F(2, 56)=25.783, p<.001, η2 =.479), but no significant
differences in the gender factor (F(1, 28)=2.240, p=.146, η2= .074) or the interaction effect (F(2, 56)=0.680, p=.511, η2= .024). Multiple comparisons with the Bonferroni method
revealed a significant difference for the distance factors:
proposed > intimate (p=.040), proposed > touch (p<.001), andCopyright (c) 2018 IEEE. Personal use is permitted. For any other purposes, permission must be obtained from the IEEE by emailing pubs-permissions@ieee.org.

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intimate > touch (p<.001). Therefore, the participants
perceived more humanlike-ness about the reaction distance inthe proposed condition than in the alternative conditions;prediction 1 was supported.
B. Verification of Prediction 2
Figure 10 shows the questionnaire results about thenaturalness of the reaction distance. We conducted a two-factor
mixed ANOVA for the gender and distance factors, and theresults showed significant differences in the distance factor(F(2, 56)=71.493, p<.001, η2 =.719). We found a significant
trend in the gender factor (F(1, 28)=3.891, p=.058, η2 = .122)
but no significant difference in the interaction effect (F(2,56)=0.579, p=.564, η2 = .020).
* : p <.05 *** : p <.001

***

7

*

6
5
4
3

2
1
Touch
(0cm)

Proposed(20cm)
Male

Intimate(45cm)

FemaleFig. 9. Questionnaire results of humanlike-ness of reaction distance: Only
significant differences compared to proposed conditions are shown.

****** : p <.001

***

7
6
5

4
3
2
1
Touch
(0cm)

Proposed(20cm)
Male

Intimate(45cm)

FemaleFig. 10. Questionnaire results of naturalness of reaction distance: Only
significant differences compared to proposed conditions are shown.

***

7

***

*** : p <.001

6
5

4
3
2
1

Touch
(0cm)

Proposed(20cm)
Male

Intimate(45cm)

FemaleFig. 11. Questionnaire results of total feelings: Only significant differencescompared to proposed conditions are shown.

Multiple comparisons with the Bonferroni method revealed
a significant difference for the distance factors: proposed >intimate (p<.001), proposed > touch (p<.001), and intimate >touch (p<.001). The participants perceived more naturalness
about the reaction distance in the proposed condition than thealternative conditions; prediction 2 was supported.
C. Verification of Prediction 3
Figure 11 shows the questionnaire results about their overall
feelings of the robot. We conducted a two-factor mixed
ANOVA for the gender and distance factors, and the results
showed significant differences in the distance factor (F(2,56)=21.658, p<.001, η2 =.436) and the gender factor (F(1,28)=4.324, p=.047, η2 =.134) but no significant differences in
the interaction effect (F(2, 56)=1.129, p=.331, η2 = .039).
Multiple comparisons with the Bonferroni method revealed
a significant difference for the distance factors: proposed >intimate (p=.007), proposed > touch (p<.001), and intimate >touch (p<.001). The participants evaluated the robot more
highly in the proposed condition than in the alternative
conditions; prediction 3 was supported.
VI. DISCUSSION
A. Implications
Our study clarified the minimal comfortable distance towarda potential touch around a face by observing human-humaninteraction and investigated whether a robot should react
before being touched by a person by following the minimum
comfortable distance of people. For the former result, even if
we only conducted a data collection with Japanese participantsof certain ages, our analysis of the gathered data offers enoughscientific contribution to both the human-human andhuman-robot interaction communities. For example, eventhough several famous researches (which provided such humanbehaviors as proxemics, e.g., personal space [16], modeling ofparticipation roles [50] [51] and Midas-touch effects, e.g.,
prosocial behaviors caused by a touch [52]) investigatedlimited situations, they provided basic knowledge that
contributed to the knowledge building process inhuman-human interaction[43-45] and human-robot
interaction [23-30] studies. With the scientific findings fromour current study, people can better ponder which distancethresholds are appropriate for different kinds of robots,different situations, cultural effects, and so on.
For the second point, our experiment results showed thatpre-touch reaction behaviors play critical roles in the perceived
feelings of robots. People preferred a robot that reacts at a
certain distance before a potential touch more than a robot thatreacts after being touched, and establishing an observed
minimum comfortable distance from people was preferred overexisting distance thresholds based on conversation situations.
Such different preferences to pre-touch reactions might becaused by the mental model held by people to our robot’s
human-like appearance. People might assume that since therobot has human-like capabilities to being touched, they prefera robot that reacts before being touched as people do. Of course,
distance knowledge may not be applicable for quite different
kinds of robots, especially pet types that don’t have

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This is the author's version of an article that has been published in this journal. Changes were made to this version by the publisher prior to publication.
The final version of record is available at
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SHIOMI et al.: PRE-TOUCH REACTION DISTANCE FOR ROBOT’S FACE
non-humanlike appearances. In other words, pre-touch reaction
behaviors should mimic people’s mental models of robots thatcan be changed due to appearances and cultural differences [53,54]. For example, if we use for touch interactions a simpler
robot, such as a ball-type model, an appropriate reaction
distance to a potential touch might change. When people’s
hands did not approach within the view of a human-like robot,
e.g., trying to touch it from behind, reacting after being touched
is better, even if it can technically detect people’s touch
regardless of its face direction with additional sensors, such asembedded depth sensors.
B. Gender Effects
The experiment results in human-robot interaction showed asignificant trend about the naturalness of the reaction distancein the gender factor, where female participants are more
inclined to judge the robot’s behavior as natural. Moreover, as
shown in Tables I and II, the comfortable minimum distancefrom a person of the same gender is slightly smaller than fromthe opposite gender, even without significant differences. Two
reasons might explain these phenomena. Past studies showedthat females are more receptive to being touched or toclose-distance interaction than males, and they also deem asame-gender touch as more acceptable than an opposite-gender
touch [43-45]. To investigate the effect of the robot’s gender on
the naturalness of the reaction distance, using a different
android with a male appearance is needed.
A past study provided several guidelines for touch interaction
design between people and robots, including gender effects[55]. Even though we found no significant differences about
the minimum comfortable distance and feelings, the genders of
the touchers and the evaluators influenced their touch
interactions. Since the past study did not focus on the minimum
comfortable distance for touch interaction [55], we believe that
our current study will contribute to such guidelines from a
distance-threshold perspective based on actual observations ofhuman-human interaction.
C. Limitations
On the other hand, we need to carefully contemplate theexperiment results of this study. Since we only used a specificandroid robot with a female appearance, to generalize ourexperimental results we must test different types of androids:
male appearances, female appearances of different ages,
non-humanlike and/or such gender-neutral appearance robots
as Pepper. Investigating the touching of other body parts(shoulders or hands) would also enrich our knowledge about
pre-touch reaction distances.
Moreover, the relationship and context in touch interactions
influence the minimum comfortable distance, e.g., a robot thatis used as a home-assistant might build friendly relationships
with users through long-term interaction, and their distancemight become shorter. In addition, in this study the robot only
showed a simple reaction. If it hesitated to being touched, even
if the distance is not human-like, such feelings will increase,and the total feeling might decrease.

7VII. CONCLUSION

In this study, we focused on pre-touch proxemics in thecontext of human-robot touch interactions. For human-likereactions for robots that are being touched, first we conducted adata collection to identify the minimum comfortable distancein human-human touch interactions. Data analysis from thepre-touch interaction data showed that the average minimum
comfortable distance is 20 cm between faces and the hands ofothers.
To enable our robot to react to being touched at thatminimum comfortable distance, we implemented a depth
sensing system to measure the distance between a robot’s faceand a human hand. We experimented with 30 participants toinvestigate whether the robot should react before/after being
touched and whether its reactions should adhere to theobserved minimum comfortable distance of people. We
compared three reaction distances for the robot to being
touched: 0 cm as an actual being touched distance, 20 cm as anobserved minimum comfortable distance in human-humantouch interaction, and 45 cm as an intimate distance inconversation situations.
We found that a robot that reacts before being touched wasevaluated more highly by the participants than a robot thatreacts after being touched. A robot that reacts at the humanminimum comfortable distance (20 cm) was evaluated more
highly than a robot that reacts at the intimate distance (45 cm).
This knowledge will contribute to building pre-touchproxemics and designing reaction behaviors for social robots
when they might be touched by interacting partners.
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