The final publication is available at
http://dl.acm.org/citation.cfm?id=2658873

User-friendly Autonomous Wheelchair for Elderly Care
Using Ubiquitous Network Robot Platform
Masahiro Shiomi, Takamasa Iio, Koji Kamei, Chandraprakash Sharma, and Norihiro Hagita
ATR Intelligent Robotics and Communication Laboratories
2-2-2 Hikaridai, Keihanna Science City, Kyoto, Japanm-shiomi@atr.jp, iio@atr.jp, kamei@atr.jp, chandraprakash@atr.jp, hagita@atr.jp
ABSTRACTThe importance of assistive robots for elderly people isincreasing to match the needs of rapidly aging worldsocieties. This paper develops a wheelchair robot to support
the movement of the elderly to decrease caregiverworkloads from the perspective of physical load and time
consumption. We observed the behaviors of caregivers at a
private residential care home when they are wheelingelderly people in wheelchairs. The behavior includes
appropriate utterances for reducing the anxieties of seniorcitizens based on properties of place, e.g., “Here the path isa little narrow” while passing a narrow space or “Now let’s
go into elevator.” They also adjusted to the wheeling speed
preference of each individual because their preferred speeds
were different. We implemented these two functions for
elderly care using the Ubiquitous Network Robot Platformthat allows the management of users and environment
properties. Experimental results with elderly participants at
a pseudo resident home show that the seniors prefer awheelchair robot on which the above functions have been
implemented.
Author Keywords

Autonomous Wheelchair; Human-Robot interaction;
Ubiquitous Network Robot Platform
ACM Classification Keywords

I.2.9. Artificial Intelligence: Robotics
INTRODUCTION

As the number of senior citizens continues to increase inmany countries including Japan, Italy, and Germany,
assisting them is one of the major purposes of robotics
research field. Such physical assistance as walking aid [1,2] and carrying baggage [3] are especially promising
applications for assistive robots.
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Recent research has also focused on the social acceptanceof assistive robots due to the advances in their development.
Even if stable and safe wheelchair robots are realized,
integrating them in the world is difficult without acceptanceby the actual users: elderly people. Such a gap between
researchers (or engineers) and users is always experienced
when new technologies are introduced to the world.
User-friendliness is one key for acceptance from elderly
people. Assistive robots must consider both their individual
properties and their preferred interaction style. For example,
the walking speeds of seniors vary widely and tend to be
slower than younger people. Therefore, assistive robots that
accompany users need a function to adjust their moving
speed based on each elderly person’s preference. Moreover,a past research work reported that elderly people prefer aconversational robot more than a non-conversational one[4]. Such behavioral considerations are useful to design
assistive robots for the elderly.
We are developing a moving support system using awheelchair robot for the benefit of the elderly. We analyzed
the typical behaviors of caregivers in a private residential
care home. Such behaviors include appropriate utterances toreduce the anxieties of the elderly that reflect the places andchanging wheeling speeds based on individual preferences.
To implement typical behavior in a wheelchair robot that
adapts to such personal properties as a preferred walking
speed, we employed a Ubiquitous Network Robot Platform(UNR-PF) service, which manages interaction between
users and wheelchair using UNR-PF. It also manages
environment information such as the spatial attributes of acorridor; the robot used this information to makeappropriate comments to reduce stress, as caregivers do(Fig. 1). We experimentally evaluated the effectiveness ofthese functions with elderly participants at an experimental
private residential care home facility.

“Now, we passing
through a narrow
hallway”

Fig. 1 Wheelchair robot with an elderly person

The final publication is available at
http://dl.acm.org/citation.cfm?id=2658873

RELATED WORK

Assistive robots for elderly people are seeing greater
development in the world. For example, researchers havedeveloped them as walking aids [1, 2]. Mutlu et al.
developed a conveyance robot to assist hospital staffs,
which indirectly assists elderly people [6]. Developing awheelchair robot is one straightforward approach tophysically support elderly people [7]; such basic navigation
methods as path planning [8], obstacle avoidance [9], andsimultaneous localization and mapping [10, 11] arestabilizing due to the hardware and software advances ofwheelchair robots. Therefore, researchers are focusing on
various stages of research, e.g., such as a user interface as avoice interface [12] and a brain machine interface [13] foreasily controlling wheelchair robots, comfortable driving byconsidering human perceptions [14], and safe autonomous
navigation for multiple wheelchairs [15].
Related to the development of such physical assistant robots,social robots, which focus on effective communication withthe elderly, are also becoming a major topic in this research
field. For example, social robots have been developed for
healthcare assistance that give verbal instruction to provide
reminders about medicine schedules [16, 17]. Paro, a seal
robot, is used for therapy purposes in elderly care homes[18]. Iwamura et al. investigated the effectiveness of theconversation and the appearances of a physical assistantrobot for elderly people [4] and concluded that seniors
prefer a conversational robot as a shopping assistant partner.
Similar to these related works, in this research weinvestigate the effectiveness of a wheelchair robot thatprovides moving support to elderly people instead of
caregivers through an experiment with actual elderly people.
One of the unique points of our research work is its
investigation of the perception of elderly people about two
implemented functions that were designed by observing the
behavior of actual caregivers for such moving support as
speaking behavior for wheelchair robots. Past related works
developed several wheelchair robots to provide moving
support [7], but they did not focus on such perceptions.

We observed how the caregivers wheeled the elderly people
around the home. From ten observations of a 11-m hallway
between an elevator and a dining hall/cafeteria, the average
wheeling speed was around 600 mm/second, which
resembles the slow walking speed of an adult. Caregivers
often made comments based on the locations or about
arriving at or waiting for the elevator or entering thecafeteria/recreation room, even if the elderly people did not
respond.
After observing the caregiver behaviors during the moving
support, we discussed them with the home’s administrator.
Even though the caregivers carefully maintained a slow
wheeling speed, we learned that some of the elderly people
desire an even slower wheeling speed because they want tomove at their own walking speed. The administrator alsoemphasized that caregivers must engage in small talk tohelp reduce the anxiety of the seniors, even if they failed torespond.
Based on these observations, we implemented twofunctions to realize a friendly wheelchair robot for moving
support: 1) adaption of moving speed based on individual
preference and 2) small talk about position-related events.
System Overview

We used an UNR-PF to manage the preferred speed of theindividuals as a personal characteristic and environmental
information to support position-related events to implement
the observed functions. Fig. 2 shows an overview of thesystem, which consists of three components: user interface(UI), UNR-PF, and a wheelchair robot. The details aredescribed as follows.
Wheelchair robot
Elderlyperson

UNR-PF
UI

or

Caregiver

SYSTEM DESIGN AND OVERVIEW

Task manager

Task executor

Laser range
finders

Localization

Map data

Path planning

User data

Obstacle
avoidance
Speedcalculation

Speechsynthesis

Fig. 2 System overview

Design Policy for a Wheelchair Robot

We investigated how actual caregivers interact with theelderly at a private resident home (Good Time Living
Kōrigaoka, Osaka) to design the functions for ourwheelchair robot. About 100 elderly live in the home,among whom 20 only use wheelchairs every day.
The minimum number of daily wheelchair trips for a personin the home was 10: six times between the bedroom and thedining area (three round trips for meals), twice between the
bedroom and the bathroom, and twice between the bedroom
and the recreation room. Therefore, at least 20*(10-times)
wheelchair uses for the moving support of elderly people
occur in this home.

User Interface

We used an Android tablet (Nexus 7) to control thewheelchair robot. The user interface consists of threepanels: settings, user selection, and navigation (Fig. 3). By
using a “login” system, the system automatically retrievesand changes the moving speed of the wheelchair robot tothe preferred speed of the user who is riding on the robot
wheelchair. Destination options are displayed by simple
icons that the elderly or the caregivers can touch to select atarget location.

The final publication is available at
http://dl.acm.org/citation.cfm?id=2658873

for details). We used the UNR Platform to connect thewheelchair robot and a client user interface system and to
manage both the elderly and environment information.
Wheelchair Robot

Fig. 3 UI to determine wheelchair location
Service application
layer

Service 2

Service 1

Global platform
Map

User

Robot

Resource
management

UNR-PF layer

Operator

Statemanagement

Local platform(place B)

Local platform (place A)
Map

User

Resource
management

Component 1

Robot

Operator

Statemanagement

Component 2

Service

Messagemanagement

In this work, we used a differential drive robotic wheelchairfrom Nissin Medical Industries (NEO-PR45, Fig. 1), whichis equipped with three laser range finders (Hokuyo UTM30LX). It is 59-cm wide, 85-cm-tall, and 104-cm-long and
we set it to move forward at a maximum velocity of 900
mm/sec and at 30 degree/sec. The forward acceleration andthe rotation are 600 mm/sec2 and 30 degree/sec2,
respectively. The laser range finders are used for
localization and obstacle detection. For safe navigation, we
implemented a time varying dynamic window (TVDW) [9]and used speech synthesis software, XIMERA [19], for the
robot’s speech.
For speed adaption and speaking behavior, the wheelchairrobot changes its moving speed using the preferred speed
information from UNR-PF to realize the first function. For
the second function, the robot makes pre-defined small talkbased on its position and registered map information in
UNR-PF around narrow spaces and slopes. The robot alsouses the elderly person’s name who is riding in thewheelchair and informs her of departures and arrivals.

Service

Messagemanagement

Component 3

Component 4

・・・ Component N

Robot component
layer

Fig. 4. UNR-PF overview

UNR-PFThe UNR platform is an open standard infrastructure for
networked robot services [5]. Its salient point is that it
focuses on abstraction over the underlying low level robotic
hardware layer to develop robotics services, unlike othercommon libraries and middleware such as ROS and RTM.
Even if such systems enable robotics researchers to developfunctions for robot control, it remains difficult to manage
robot service applications with different kinds ofrobots/sensors. To bridge the gap between robot
development and service applications, our UNR platform
design has three layers: service application, platform, androbot component (Fig. 4).
To achieve interoperability with different robots andsensors by sharing information among the robots and theservice applications, the specifications of the data structures
and the interfaces must be standardized. Even though partof the UNR platform has already been proposed to several
organizations as international standards, the standardization
details are beyond the scope of our research focus (see [5]EXPERIMENT
Hypotheses and Prediction

We implemented two functions on our wheelchair robot byreferring to the actual caregiver behaviors. If thesefunctions are prepared well, we believe that the elderly willmore positively evaluate the robot than a robot withoutthem.
As an alternative method, we used a wheelchair robot
without our implemented functions that was designed basedon the observations of caregivers. The safety functions are
the same as the developed system. The moving speed is 600
mm/sec, which is the average speed of the caregivers
measured at the private residential care home. We also
prepared a caregiver condition to compare the evaluations
with the robots as an additional alternative method. Basedon the above idea, we made the following predictions:
Prediction 1: The wheelchair robot with the implemented
functions will be rated higher in terms of comfortablemoving speed than the wheelchair robot with an alternative
method.
Prediction 2: The wheelchair robot with the implemented
functions will provide more enjoyment during movement
than the wheelchair robot with an alternative method.
Participants

Twenty eight elderly people (14 women and 14 men, whoaveraged 74.0 years old, S.D 6.85) participated in theThe final publication is available at
http://dl.acm.org/citation.cfm?id=2658873

experiment. 10 people, who require daily care, are living inprivate residential care homes; five usually use wheelchairs.
One or two senior staff members from the care home also
participated in the experiment to support the elderly people
who are living in the home.

In Fig. 7, a caregiver is pushing a participant in awheelchair.

Environment

We conducted the experiment in an experimental residential
care home facility that consists of a bedroom, a bathroom
and a lobby. The room sizes and designs are the same as theactual care home where some of the participants are
actually living. Fig. 5 shows a map of the environment.
Conditions

We used a within-participant experiment design to evaluate
and compare the effects of the implemented functions.
Simple navigation condition

In this condition, the wheelchair robot automatically moved
with the participants who are riding on it after selecting thetarget location by UI. As written above, the wheelchair’s
usual speed was 600 mm/sec. The robot did not use its
speech synthesis function. Fig. 6 shows a wheelchair robot
moving around in the experimental environment.
Proposed condition

Bedroom

5m

ToiletBathroom

12 m

Fig. 5 Environment

In this condition, the wheelchair robot also automatically
moved after selecting the target location by UI. It speaks
based on the robot’s location. We adjusted the usual speed
to each participant’s preferred speed that was measured at
the beginning of the experiment (details are described
below).
We set two kinds of place information in this environment:a narrow place at the bedroom’s door and a slope in front of
the bathroom. This information was sent to the robot fromthe UNR-PF using the robot’s position, and then the robot
says pre-defined dialogues before passing these places. For
example, the robot said, “here is relatively narrow” before
passing the bedroom’s door, and “now we are going slightly
uphill” at the beginning of the slope. Fig. 1 shows a scene
where a wheelchair robot speaks before passing the door.

Fig. 6 Wheelchair in simple navigation condition

Caregiver condition

In this condition, a caregiver wheeled the participants as the
caregivers usually do. Therefore, this condition reproducesa daily situation of the elderly who are using wheelchairs
and need help to move around.
If the participants were living in the care home, a staff
member of the home wheeled them in the experiment in theusual fashion; we did not specify moving speed orconversation behavior. For the rest of the participants, theexperimenter wheeled them at around 600 mm/sec, which isthe average speed at which the caregivers wheeled theelderly people, as measured by the private resident home.
The experimenters talked to the participants using similar
contents to the proposed condition that was described above.

Fig. 7 Caregiver condition

The final publication is available at
http://dl.acm.org/citation.cfm?id=2658873

7

movement. All questionnaire items were evaluated on a 1to-7 point scale.

6
5
4

RESULTS

3

Verification of Prediction 1

7

Figure 8 shows the result of the comfort of the moving
speed. We conducted a one-factor within subject ANOVA
and found a significant difference among the conditions (F(2, 52) = 10.419, p<.001, partial η2=.286). Multiple
comparisons with the Bonferroni method revealed
significant differences: caregiver > simple navigation (p= .001) and proposed > simple navigation (p = .001). No
significance was found between caregiver and proposed (p= 1.0). Therefore, prediction 1 was supported.

6

Verification of Prediction 22
1
Simple navigation

Proposed

Caregiver

Fig. 8 Comfort of moving speed

5
4
3
2
1
Simple navigation

Proposed

Caregiver

Figure 9 shows the result of enjoyment during the
movement. We conducted a one-factor within subject
ANOVA and found a significant difference among theconditions (F (2, 52) = 12.026, p<.001, partial η2=.316).
Multiple comparisons with the Bonferroni method revealed
significant differences: caregiver > simple navigation (p= .029) and proposed > simple navigation (p <.001). A
significant trend was found between proposed andcaregiver (p = .096). Therefore, prediction 2 was supported.

Fig. 9 Enjoyment during movement
Procedure

Before the first session, the participants were given a brief
description of our experiment’s purpose and procedure. We
also determined their preferred speed; the participants rodein the wheelchair robot at three different speeds: 300, 600,
and 900 mm/sec. Most of the preferred speeds reported by
the participants are used for controlling the wheelchairrobot under the proposed condition. Seven participantspreferred 300 mm/sec, 19 preferred 600 mm/sec, and two
preferred 900 mm/sec.
Since the experiment had a within-participant design, eachparticipant participated in three sessions of different
conditions. The order of the conditions wascounterbalanced. Staff members remained in theenvironment for safety and to record videos. The
participants filled out a questionnaire after each session.
The experiment’s route was designed based on the daily
situation of a representative elderly person who is using awheelchair at the private resident home in the evening. She
leaves her bedroom to go to the bathroom to take a bath andreturns to her bedroom. Since this is an experiment, thewheelchair robot makes a round trip between the bedroom
and the bathroom.
Measurements

We measured two items in this experiment: comfort at thepreferred moving speeds and enjoyment during the

DISCUSSION
Limitations

Since this study was conducted for moving support at anexperimental residential care home in Japan, we cannot
generalize about our predictions from it. Even though thisexperiment was held in a realistic situation with participants
who used the wheelchair robot, it was conducted within theframework of an academic study. The elderly participants
only used the wheelchair robot a few times. Thus, the effectshown in the experiment would probably be moderated ifthey got accustomed to the wheelchair robot: thediminishment of any novelty effect. For example, the robot
needs to change its words to avoid negative impressions
caused by repeating the same speeches. The preferred speedof individuals might also change based on experiences withthe wheelchair robots. These limitations of our study will betested in the future, perhaps with the realistic deployment ofwheelchair robots in society.

CONCLUSION

This paper investigated whether elderly people prefer awheelchair robot that makes comments based on place
while providing moving support and changes its moving
speed according to individual preferences. To implement
these functions, we used a wheelchair robot and UNR-PF,
which can manage individual properties and environment

The final publication is available at
http://dl.acm.org/citation.cfm?id=2658873

information for robot services. We conducted anexperiment with elderly people at an experimental
residential care home that consists of a bedroom and abathroom. The elderly people more highly evaluated awheelchair robot with the implemented functions than awheelchair robot without them; we found no significant
differences from the questionnaire results between
caregiver support and the wheelchair robot with our
implemented functions.

ACKNOWLEDGMENTS

This research was supported by the Ministry of Internal
Affairs and Communications of Japan and JSPS KAKENHI
Grant Number 25730165. We thank the staff at the ORIX
Living Innovation Center and the Good Time Living
Kōrigaoka for their helpful participation. We also thankShinobu Masaki, Naoki Kusakawa, and Eiko Fukumori for
their help.

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