Investigation of an Autonomous Mobile Robot’s
Avoidance Motion for Pedestrian and Observer Comfort
in a Hospital Environment
1

Fumiya Ohnishi, 2Yosuke Kawasaki, 3Masaki Takahashi

1 Graduate School of Science and Technology, Keio University

3-14-1 Hiyoshi, Kohoku-ku, Yokohama 223-8522, Japanfumiya-onishi@keio.jp
2Graduate School of Science and Technology, Keio University
3-14-1 Hiyoshi, Kohoku-ku, Yokohama 223-8522, Japan
3Department of System Design Engineering, Keio University
3-14-1 Hiyoshi, Kohoku-ku, Yokohama 223-8522, Japan

1

Introduction

In recent years, there is a growing demand for autonomous mobile robots to transport
medical instruments in hospitals. This is because autonomous mobile robots are expected to improve the quality of medical services by replacing the transportation tasksof medical staff, allowing them to spend their time on more specialized tasks such as
keeping an eye on patients and medical examinations[1][2].
For a robot to be accepted by coexisting people, it is important that they feel comfortable about coexisting with the robot [3]. It has been shown that factors related to therobot’s motion, such as the robot’s motion trajectory and the distance between the robot
and humans, have a significant impact on people’s comfort [3]-[6]. Therefore, autonomous mobile robots in human coexistence environments need to avoid pedestrians in a
comfortable manner.
Specifically, coexisting people can be divided into pedestrians and observers. As aconcrete example, Figure 1 shows a pedestrian (a patient) and an observer (a medical
staff member keeping an eye on the patient) in a hospital. It is notable that it is importantfor pedestrians to feel comfortable when they pass by the autonomous mobile robot,
and for observers (people who observe the robot’s movements from a third-person perspective) to feel comfortable observing the robot’s movements. Particularly in hospitals, it is important for medical staff to keep an eye on patients, so it is important forthem to have a comfortable impression of the robot’s motion when it passes by a patient,in order for the robot to be accepted in the field. Therefore, the aim of this study is toinvestigate a robot’s pedestrian avoidance motion that provides a high level of comfort
for both the pedestrian and the observer.
The pedestrian’s level of comfort in relation to the robot’s motion has been investigated in previous studies. Pacchierotti et al. [7] considered the comfort of a robot’s
motion when avoiding and passing a pedestrian walking straight along a corridor. They
designed an avoidance motion to achieve the desired pedestrian-robot distance when
passing a pedestrian, and investigated the pedestrian’s level of comfort with respect toadfa, p. 1, 2011.
© Springer-Verlag Berlin Heidelberg 2011

Observer

Robot

Pedestrian

Fig. 1. Pedestrian (patient) and observer (medical staff) in a hospital. It is important for thepedestrian to feel comfortable when they pass by the autonomous robot, and for the observer
to feel comfortable when observing the robot’s movements.

the distance when passing a pedestrian. They found that the pedestrian’s level of comfort decreased when the passing distance was short. Neggers [8] et al. investigated theeffects of the distance between the pedestrian and the robot and the speed of the robot
on the pedestrian’s level of comfort when the robot and the pedestrian pass each otherin parallel and in a straight line. They found that the farther the distance between thepedestrian and the robot and the slower the robot’s speed, the greater the pedestrian’slevel of comfort. However, no previous studies have investigated not only pedestrians’
but also observers’ level of comfort in response to a robot’s pedestrian avoidance motion.
Therefore, the aim of this study was to investigate pedestrians and observers in a
hospital environment to find out how comfortable they feel with the robot’s pedestrian
avoidance motion. An experiment was carried out in a hospital to investigate the impression of medical staff on the comfort of the robot’s movements from the perspectiveof pedestrians and observers.

2

Assumed workflow

This chapter describes the assumed workflow when introducing a hospital transport
robot and the positioning of this research. First, the medical staff goes to the location
where work needs to be done and gives voice instructions to the robot via an intercom
about the destination and the item to be transported (e.g. take nappies to room A2). The
hospital transport robot uses the staff station as its base, and when it receives instructions from the staff, it moves to the destination where staff are waiting to be transported,such as individual patient rooms, toilets or the linen cupboard for restocking. In theinitial phase of operation, it is assumed that the robot will be responsible for transporting nappies and sheets, which do not need to be differentiated for each patient. The
workflow described above is expected to eliminate the need for staff to make roundtrips to transport instruments, allowing them to provide more care and attention to patients, and to improve to a more efficient workflow using a robot.
In the corridor where the robot moves while transporting instruments, it passes pedestrians. This research aims to ensure that the robot’s pedestrian avoidance motion
when passing pedestrians is highly comfortable to pedestrians and observers.

3

Robot design

3.1

Robot configurations

An overview of the autonomous mobile robot used in this experiment is shown in Figure 2. The robot is a model of the WHILL Model CR [9] electric wheelchair manufactured and sold by WHILL.Inc, to which sensors and computers have been added toenable the acquisition and processing of information necessary for navigation. The
added sensors are 2D LiDAR (Hokuyo UST-20LX-H01), 3D Li-DAR (Velodyne
VLP-16) and a stereo camera (Intel Realsense D455). The system provides a 360-degree view of the environment by integrating the 3D point cloud information of surrounding obstacles obtained from these sensors. The performance and application of
the additional computers were as follows: Lenovo LEGION (Intel Core i7 12700H,
16GB RAM, RTX 3070): for global path planning, Fujitsu LIFEBOOK (Intel Corei7-1355U, 32GB RAM): for planning pedestrian avoidance motion, Jetson AGX Orin:for all other processing.
The pedestrian avoidance motion was planned based on the surrounding obstacle
information and the self-position information. The surrounding obstacles was obtained by the 3D point cloud information described above, and the self-position
Intel
Realsense
D455

PC
Robot
Intel
Realsense
D455

Sensor

VLP-16

Jetson AGX
Orin
LRF

Whill
Model CR

HokuyoUST-20LX

Fujitsu
LIFEBOOK

Fig. 2. Hardware configuration of the robot used in the experiment

LenovoLEGIONinformation was obtained by 3D LiDAR-based self-localization. Details of the pedestrian avoidance motion planning are described in the next section.
3.2

Pedestrian avoidance method

In this study, a method based on state space sampling [10], which is used to generate
natural motion that is predictable to humans, is implemented. Specifically, multiple
lanes parallel to the global path are defined, multiple candidate lane-changing paths inposition space are sampled, and the optimal path is selected. The details are described
below.
First, the generation of candidate paths is described. As shown in Figure 3, multiple
lanes L parallel to the global path are defined and a lane change path consisting of aclothoid curve is generated for each lane. Each lane is generated at intervals of Δl [m]until the change distance from the global path is lmax [m]. The approximate shape of thelane change path is determined by the forward distance dforward [m] and the change distance lchange [m] shown in Figure 3. The lane change paths and lanes are then discretized
into a sequence of points and combined to generate a candidate path Pi.
Next, the selection of the optimal candidate path and the calculation of the speed command value are explained. Select a candidate path Pi* that minimizes the following
evaluation function Ji.

()

J i = wgoal d goal,i − d col,i + wlane d lane,i max ( d lane,i )
iL

(1)

Pi* = arg min J iiLwhere dgoal,i is the distance to the goal of Pi, dcol,i is the distance to collision with an
obstacle on Pi, dlane,i is the distance between the lane of Pi and the current lane, andwgoal, wlane are the weights. Therefore, the candidate path that is most progressive towards the goal, i.e. avoids pedestrians and changes to the nearest lane is selected. The
selected path is then followed by the Pure Pursuit algorithm [11] to calculate the speedcommand values.

Lane change path

Global pathLane

dforward

lchange

dobs
Fig. 3. Parameters of the pedestrian avoidance motion

Δl
lmax

3.3

Robot motion in the experiment

In this experiment, the robot and the pedestrian first faced each other and started moving simultaneously. Then the pedestrian and the robot moved straight ahead, and when
the distance between the pedestrian and the robot became smaller than the avoidance
start distance dobs [m], the robot changed to a lane where the pedestrian could be avoided
based on the pedestrian avoidance method described above, and passed each other.

4

User study design

In this section, the design of the subject experiments is described. The experiment wasapproved by the Bioethics Committee of the Faculty of Science and Technology, Keio
University. Approval No. 2023-030.
The experiment was conducted in the space in front of the staff station on the 6th
floor (hospital floor) of the Nagasaki Rehabilitation Hospital [12]. Six medical staff(two males and four females) participated in the experiment. The six subjects are referred to as M1, M2, F1, F2, F3, and F4, respectively.
The experimental scene is shown in Figure 4. As shown in Figure. 4, a medical staff
member passed the robot as a pedestrian and a medical staff member observed the robot’s pedestrian avoidance motion as an observer. The pedestrian and observer were
each asked about their level of comfort with the robot’s pedestrian avoidance motion.
The experimental procedure is described below. The experiment was conducted by
two staff members: one who participated in all the experiments (M2) and a newly called
staff member (P: M1, F1~F4). The experiment was conducted as follows: after calling
P, P was asked to pass the robot and P was asked about his/her level of comfort fromthe pedestrian’s point of view and M2 was asked about his level of comfort from theobserver’s point of view. Next, P was asked to observe the robot passing M2 at the
moved position, and the level of comfort from the observer’s perspective was heard
from P and the from the pedestrian’s perspective was heard from M2. The experimental
design of the robot moving back and forth reduced the time required to position the
robot and was therefore designed to be friendly to the medical staff on duty. The timerequired per person was set at 15 minutes and the number of trials was flexibly increased or decreased depending on the remaining time and the experimental situation.
The robot’s motion parameters were those given in Table 1, where vmax is the maximum
translational velocity, amax is the maximum translational acceleration, ωmax is the maximum angular velocity, αmax is the maximum angular acceleration and f is the control
frequency.
The evaluation indices are described below. In this study, the level of comfort withthe robot’s motion was assessed using a 7-point Likert scale questionnaire. Specifically,
for the question “I feel comfortable in the robot’s motion”, “I feel comfortable” was set
to 1 and “I do not feel comfortable” was set to 7.

Observer

Pedestrian

Robot

Fig. 4. Experimental scene

Table 1. Parameters used in the experiment5

Parameter

Value

ParameterValuel [m]
lmax [m]dforward [m]vmax [m/s]
amax [m/s2]
max [rad/s]

0.10
1.0
2.0
0.50
0.80
0.40

 max [rad/s2]
d obs [m]

0.80
10.0
2.0
8.0
20
-

wgoal
wlane
f [Hz]-

Results and discussions

In this experiment, a total of ten passing movements were performed and analysis was
performed on a total of six data sets, excluding one data set in which the subject had torepeat the evaluation and three data sets in which the robot’s motion became oscillatory
before the passing movement was performed and the level of comfort evaluation forthe pedestrian avoidance motion could not be obtained. When analyzing the relationship between the robot’s pedestrian avoidance motion and the level of comfort evaluation of the pedestrian and the observer, the distance l between the pedestrian and therobot and the robot’s pose angle θ when the pedestrian and the robot pass each otherare taken as the feature values of the pedestrian avoidance motion, as shown in Figure
5 (i). The reason is that l is an index that has been investigated in previous studies toevaluate the level of comfort of mobile robot motion, and θ represents the progress ofthe pedestrian avoidance motion. When θ is large, the robot is changing lanes, and when
θ is close to 0, the robot is following a lane.

θ

θ
l

l
observer

robot

robot

pedestrian(i) Feature values of pedestrian avoidance motion l, θ(a) pedestrian(b) observer(ii) l-θ plot of questionnaireFig. 5. Relationships between questionnaire and robot pose θ, distance l

Figures 5 (ii)-(a) and (b) show scatter plots representing the level of comfort of pedestrians and observers for l and θ. It can be seen that for both pedestrians and observers, especially for observers, a point of low level of comfort occurs when θ is large.
Note that a large θ indicates that the pedestrians have passed each other during a lanechange. Since the value of l does not change much in any trial, i.e. when passing during
a lane change, the pedestrians’ and observers’ level of comfort tends to decrease when
θ is large, regardless of the value of l. This result suggests that it is important not only
to increase the distance between the robot and the pedestrian when passing as the previous studies have shown, but also to design the robot to pass the pedestrian after thelane change.

6

Conclusion

This study investigated the pedestrian avoidance motion of an autonomous mobile robot with a high level of comfort. In particular, because it is important for medical staff
to keep an eye on patients, the level of comfort was studied not only from the perspective of the pedestrian, which has already been studied, but also from the perspective of
the observer, who observes the robot’s movements from a third-person perspective. The

experiment was conducted in a real hospital, where medical staff were asked about theirlevel of comfort from the pedestrian’s and observer’s perspective in relation to the robot’s pedestrian avoidance motion. The level of comfort of the robot’s pedestrian avoidance motion was analyzed by examining the relationship between the feature values ofthe pedestrian-robot distance l and the robot pose angle θ as the pedestrian and the robot
passed each other. While the value of l did not change much in any trial, impression of
low comfort was observed for both pedestrians and observers, especially for observers,
as θ increased. That is, when passing each other during a lane change, the comfort ofthe pedestrian and the observer tended to decrease regardless of the pedestrian-robot
distance.
In the future, we would like to develop a pedestrian avoidance method designed topass pedestrians after a lane change. In addition, we would like to conduct a demonstration experiment in which medical staff collaborate with a hospital transport robot ina hospital, and investigate changes in medical staff workflow as a result of the introduction of a hospital transport robot.

Acknowledgments
This work was supported by Core Research for Evolutional Science and Technology(CREST) of the Japan Science and Technology Agency (JST) [grant number
JPMJCR19A1].

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