Development of the Shortest Path Display System Using Swarm LED
Indicators Based on Signal Strength of Wireless Communication
Yoshiaki Katada1 and Kazuki Kogo1
Abstract— Our research group has proposed swarm robotics
network which searches a target cooperatively. Once a robot
detects a target, robots immediately communicate with a basestation via intermediate relay robots due to the multihop
transmission of wireless communication. In this study, wedeveloped the shortest path display system between the targetand the base station based on the received signal strength ofwireless communication. We conduct a series of both indoor
and outdoor experiments in order to investigate the validity ofthe developed system.

I. INTRODUCTION
Swarm Robotics (SR) [1], [2] have attracted much researchinterest in recent years. Generally, the tasks in SR are difficult
or inefficient for a single robot to cope with. Thus, youfind overlap between SR and multi-robot systems. Şahin[3] enumerated several criteria1 for distinguishing swarm
robotics as follows:• autonomy: Each robot should be physically embodied
and situated.
• redundancy: Group sizes accepted as swarms is 10 to20.
• scalability: SR system should be able to operate undera wide range of group sizes.
• simplicity: Each robot should employ cheap design, thatis, the structure of a robot would be simple and also thecost of it would be cheap.
• homogeneity: SR system should be composed of homogeneous individuals. This enhances the above 2nd and3rd criterion.
According to the last criterion, homogeneous controllers forindividuals are desirable for SR systems. Additionally, thisapproach does not assume the existence of an explicit leader
in swarm robots due to the above criteria. This results inthat a collective behavior emerges from the local interactions
among robots and between the robots and the environment.
Therefore, it is required for SR systems that individuals inswarm show various behaviors through interactions although
the individuals are homogeneous.
The typical control tasks in SR are navigation, aggregation, formation and transport requiring distributed collectivestrategies [2]. In the previous paper, our research groupcopes with a target detection problem, which is one ofnavigation problems. In this control task, several robots can
1 Yoshiaki Katada and Kazuki Kogo are with Faculty of Science andEngineering, Setsunan University, Neyagawa, Osaka, JAPAN katada @ele.setsunan.ac.jp
1 Şahin [3] claimed that these criteria should be used as a measure of thedegree of SR in a particular study.

communicate with each other via wireless communication
networks (WCN) [4], [5] due to the multi-hop transmission
to achieve collective exploration. As soon as a robot detects
a target, the information is sent from the robot to the basestation via intermediate relay robots. Therefore, all robots
should be “connected” to the base station via WCN.
This system would be applicable to victim search, seabedresources exploration and planetary exploration. In these scenarios, it would be desirable that the shortest path connectedfrom a base station to the target is visible for system users
after the system finds the target. We assume that our swarm
robots system is operated on the ground in this paper.
In this paper, we developed the shortest path display system using swarm LED indicators based on the received signal
strength of wireless communication. The paper is organized
as follows. The next section shows the wireless module
employed in this study. Section III defines the shortest path
problem in this study and briefly introduces an algorithm forshortest path search. Section IV describes the details of theshortest path display system developed in this study. Section
V and VI show the setting and results in indoor and outdoor
experiments, respectively. Conclusions are given in the lastsection.
II. W IRELESS M ODULE
In this study, wireless devices, XBee[6], were employed(Fig.1). XBees, based on ZigBee wireless standard, cancompose wireless ad hoc networks, where nodes can communicate with each other via multi-hop path. An XBee on
each robot is set as a router of the network. The wireless basestation is a laptop equipped with the same XBee as those on
the swarm robots. The XBee equipped on the base station isset as a coordinator. The API of the above wireless devices2
can display the structure of wireless communication network(WCN) with link quality indication (LQI)3 values among all
the nodes (Fig.2). In addition to this, this can export the dataon the WCN including the LQI values among all the nodes(Fig.3).
III. D IJKSTRA’ S ALGORITHM
The XBee API provides the structure of WCN with LQIvalues as mentioned in the previous section. Such a structureof WCN is described as a directed graph with non-negative
weights, where a node corresponds to a wireless moduleand a weight value corresponds to the distance information
2 Digi International Inc. provides a software, Next Generation XCTU[6]3 The LQI is calculated from the value of the received signal strength inthe API.

Fig. 3.
Fig. 1.

Wireless module: XBeeTABLE IE XAMPLE OF ADJACENCY MATRIX
node No.
123456Fig. 2.

API of XBee

between wireless modules. For searching the shortest paths
between arbitrary nodes in the graph, the Dijkstra’s algorithm[7] can be applied. In order to apply the Dijkstra’s algorithm,
the weight values of the edge between nodes in a graphare required. According to this, the LQI value should beconverted into distance information. The LQI value in theXBee API is expressed over the range [0, 255]. Therefore, aweight value is calculated as follows: 256 − LQIij (LQIij ̸= 0)
10000 (LQIij = 0)
(1)
wij =
0 (i = j)where i, j ∈ {1, · · · , N }, N is the number of nodes andLQIij is the LQI between the i-th node and the j-th node.
When LQIij = 0, we set wij at a relatively big value because
the distance between the nodes would be effectively infinite.
The LQI value downward and upward between wirelessmodules are different (For example, see XX/Y Y in Fig.2).
This results in that the adjacency matrix, wij , is asymmetry.
The Dijkstra’s algorithm employs a smaller weight valueof the edge between nodes when those weight values aredifferent. However, this does not reflect the actual condition
observed in the preliminary experiment. Thus, we redefine
the adjacency matrix such as to employ a bigger weight value
between nodes (Eq.(2)).
wij = wji (wij < wji , i ̸= j)

Data exported from the API of XBee

(2)

1033
13617155

233
077
3157
44

31377
041
744

46341052855171157752045655444485450

After these steps, this adjacency matrix is symmetry (TableI).
Including the above steps, the Dijkstra’s algorithm isimplemented in Microsoft Excel/VBA (Fig.4). After a robot
detects a target and sends the information to the base station
via intermediate relay robots, the system user runs the VBA
program as follows; First, a node list is composed of all theXBee used in an experiment ((1) in Fig.4). In the node list,
the XBee equipped on the base station is designated as asource node while the XBee equipped on the robot finding atarget is designated as a destination node ((2) in Fig.4). Then,the nodes included in the shortest path are displayed after theDijkstra’s algorithm is executed ((3)(4) in Fig.4). Finally, theXML files which shows the nodes in the shortest path are
output ((5) in Fig.4).

Fig. 4. Dijkstra’s algorithm in Excel/VBA: the algorithm finds the shortest
path between a source node and a destination node.

Fig. 5.

Circuit for a LED indicator

IV. D ISPLAY SYSTEM OF THE THE SHORTEST PATH
Display system of the the shortest path in this study iscomposed of wireless modules and LED indicators. The
details are described as follows.

Fig. 6.

LED indicator composed of eight LEDs

A. Communication between wireless modules
For communication between XBee wireless modules, aformat called API frame is used in the XML files. The
wireless base station sends a message to the module to be
displayed according to the XML files obtained at final stepin the previous section. The MAC address of the wirelessdevice and the pin number of the XBee to be turned on arewritten in the message. These files are sent one by one fromthe base station to the WCN.
B. Circuit for a LED indicator
This study assumes that people trace a path to a target.
Thus, visible light is employed in order to display a path.
Considering the indoor and outdoor environment in a seriesof real experiments in this work, a functional specificationis required as follows;• visibility at a distance of 80 m indoor in the daytime,• visibility from any direction in a two-dimensional plane,• an electrical source other than the battery of a robot.
Fig.5 shows an electrical circuit designed according to theabove specification. The current supplied to LEDs is set at avalue larger than the rated current as well as the light sources
are blinked so as to increase the visibility of a light emission.
Red LEDs with a diameter of 0.01 m were employed. 8 LEDs
were arranged radially (Fig.6).
V. I NDOOR E XPERIMENT
A. Setup for Swarm Mobile Robots
Differential wheeled robots (Figs.7, 8) were used in thisexperiment. The robot’s diameter and height are approximately 0.17 m and 0.075 m, respectively. The robot isequipped with four infrared distance sensors located at thefront of the body for measuring the distance to other robots
and walls, and two infrared sensors located at both endsof the body for detecting a target. The maximum detection

Fig. 7.

Setup for mobile robots: front view

ranges of the former infrared sensor and the latter infrared
sensor are 0.3 m and 0.2 m, respectively. The robot’s processor is the Arduino microcontroller, which gets sensory inputs
and outputs signals to control two wheels through motor
drivers. The robot is equipped with an XBee. As a target,
an infrared-emitting ball is employed to make handling easy,
which is the official ball for RoboCup Junior [8]. Its infrared
rays are distinguishable from those emitted by the distancesensors described above due to the different wavelength.
An indicator lamp as mentioned in the previous section ismounted on the robot (Figs.7, 8).

Fig. 10.

Distribution of the robots just when a robot found a target

Fig. 11.

Shortest path given by Dijkstra’s algorithma target or when 1800 sec (30 min.) are performed without
receiving the message. For details, readers may refer to [9].
Fig. 8.

D. Experimental result

Setup for mobile robots: top view

B. Experimental Environment
We conducted a real experiment in the corridor of thebuilding at Setsunan University in Neyagawa (the yellow
part in Fig. 9). There are some class rooms adjacent to thiscorridor. Thus, the experimental environment is surroundedby walls. A target (an infrared-emitting ball) was placed at
the lower left corner in Fig. 9. At the upper right corner,a wireless base station was placed. The base station is a
laptop equipped with the same XBee as those on the swarm
robots as mentioned before. At the beginning of each trial,
swarm robots were always placed at the same initial position,
the lower right corner, next to the base station at randomorientations (Fig. 9).
C. Setting of the Experiments
In this control task, swarm robots explore the above
environment, detect a target located so far (around 80 m)from the base station as not in line-of-sight communicationand send a message to the base station via intermediate
relay robots. Therefore, all robots should be “connected” tothe base station via swarm robotic network mentioned inSection I. Thus, we conducted a real experiment by setting
the number of robots 16 [10]. One trial ends either when thebase station receives the message from the robot detecting

Fig.10 shows a sketch map of the environment with thelocation of the robots just when a robot found a target
and sent a message to the base station. Fig.11 shows theshortest path given by the Dijkstra’s algorithm. Figs.12-15
show the snapshot of the path displayed by blinking LEDs.
We confirmed that the lights were visible from the vicinity ofthe base station. We also confirmed that we can walk along
the path to the target.
VI. O UTDOOR E XPERIMENT
A. Setup for LED indicators and wireless modules
In this section, we report the results of the outdoor
experiment. The mobile robots employed in the previous
section are designed only for indoor. Therefore, only theLED indicators and wireless modules described in Section
IV were used for the outdoor experiment to demonstrate thepath display system (Fig.16). The details of the goal in thisexperiment are described in the next subsection.
B. Experimental Environment
It’s doubtful whether the path obtained in the previous
experiment is shortest because the environment was narrow.
In this experiment, the validity of the system was investigatedin the open, that is, the environment unsurrounded by walls.
We conducted the experiment in the artificial lawn groundat Setsunan University. Fig.17 shows a sketch map of theground.
C. Setting of the Experiments

6.1m

70.4m

6.3m
B

2.4m

6.1m

8.4m

3.7m

6.0m
T
82.8m

Fig. 9. Experimental setup for target detection problem (B: base station,T: target)

In this experiment, the mobile robots were not used. Thus,
the positions of a LED indicator with a wireless module were
fixed in advance. The LED indicators were arranged so thatthe shortest path between the target and the base station isapparent. Fig.17 shows the positions of the LED indicators,
where the rectangle shows a base station, the circle shows aLED indicator and the star shows a virtual target. The dashedline shows the theoretical shortest path. The number of LED

Fig. 12.

Blinking LEDs near the target
Fig. 16.

Fig. 13.

Blinking LEDs in the middle of the corridor (1)Fig. 17.

Setup for an LED indicator and a wireless module

Positions of the indicator lamps in the artificial lawn groundindicators with wireless modules was 11. We conducted theexperiment four times in the nighttime.
D. Experimental result

Fig. 14.

Blinking LEDs in the middle of the corridor (2)Fig. 15.

Blinking LEDs in the middle of the corridor (3)Figs.18-21 show the path given by the Dijkstra’s algorithm
for each trial, where the dashed line shows the given path andthe triangles show the LED indicators blinking in the path.
In all the runs, we can walk along the path to the target. The
blinking lights were visible in the nighttime. However, thesepaths were not shortest. The distances of the path obtainedin this experiment are about 1.6 times longer than the oneof the theoretical shortest path.
When we measured the LQI values, those values among
the wireless modules located inside were lower than thoseamong the wireless modules located outside. This is becausea few LED indicators located outside were included in theobtained path. We did not investigate this reason yet.

VII. CONCLUSIONSIn this paper, we developed the shortest path display
system between a base station and a target using swarm
LED indicators based on the received signal strength ofwireless communication. We employed a shortest path searchalgorithm and implemented it in our system. We confirmedthat we can trace the path obtained in the indoor and outdoor
experiments to a target. This system would be affected bynoise, e.g., interference, diffusion, diffraction and reflection
from the environment of electric wave. In future work, wewill improve our system in order to decrease the effects.
Fig. 18.

Path given by the Dijkstra’s algorithm in the 1st trial

Fig. 19.

Path given by the Dijkstra’s algorithm in the 2nd trial

Fig. 20.

Path given by the Dijkstra’s algorithm in the 3rd trial

Fig. 21.

Path given by the Dijkstra’s algorithm in the 4th trial

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