Two Mobile Robots Platforms for Experimentation: Comparison and

Synthesis

Ernesto Fabregas

, Gonzalo Farias

, Emmanuel Peralta

, Jos

e S

anchez

and Sebasti

an Dormido

Departamento de Inform

atica y Autom

atica, Universidad Nacional de Educaci

on a Distancia, Madrid, Spain

Pontiﬁcia Universidad Cat

olica de Valpara

ıso, Av. Brasil 2147, Valpara

ıso, Chile

Keywords:

Wheeled Mobile Robots, Experimental Environments.

Abstract:

This paper presents a comparison between two ready-to-use platforms developed for both teaching and re-

search purposes with wheeled mobile robots. The platforms are divided into two parts: a simulation and a real

experimental environment. In both cases, the experimental environments uses a camera and a PC (with the

corresponding software tools) as positioning sensor to locate the robots in the work-space. The comparison

includes software, hardware and usability points of view.

1 INTRODUCTION

Distributed systems are based on the idea of dividing

complex problems into coordinate actions of multiple

agents on a network that cooperate together to per-

form relatively simple tasks. In this sense, a group

of robots that can communicate between them is a

perfect scenario to test this kind of collaborative ap-

proaches.

Mobile robots are autonomous systems that can

perform different tasks. A complex task (e.g. to keep

a formation around a robot) can be divided in singles

tasks in order to perform an individual position con-

trol algorithm on each robot (Guinaldo et al., 2013).

The implementation of this kind of experiments

can be difﬁcult. First of all, we need to have a plat-

form to test these developments with real robots in a

lab. On the other hand, the complexity of the exper-

iments that can be carried out depends on the robot’s

sensors, speciﬁcally, their quality and precision. For

instance, if you want to develop obstacles avoidance,

line following, or a position control experiment, the

robot needs to know its position in running-time. This

is a problem to face in indoors environments because

the GPS does not work in this kind of situations. Be-

sides if you want to develop distributed experiments

where the robots cooperate with a common goal, then

the robots need communication to share information

(Casini and Garulli, 2016).

This paper compares two platforms developed

to implement this hands-on experiments with two

wheeled mobile robots: Moway robots (Innova, 2012)

and Khepera IV robots (KTeam, 2015). In both cases

the virtual and real experimental environments were

designed and developed considering these robots.

Both platforms have been designed for educational

purposes, but they can be used for researching pur-

poses as well.

In the ﬁrst case the simulation was developed

with Easy Java Simulations (EJS) (Esquembre, 2012).

Which is a free software tool for creation of simu-

lations in Java with a high level of graphic capabil-

ities and an increasing degree of interactivity with

JavaScript support. In the second case the simulator

used was V-REP, which is the most used simulator in

robotics nowadays (Rohmer et al., 2013).

The experimental environment has been designed

and implemented based on previous experiences of

the authors developing remote laboratories (Neamtu

et al., 2011; Chaos et al., 2013). In both cases we have

implemented an Indoor Positioning System (IPS) us-

ing the images of camera installed on the ceiling of

the lab and Swistrack (Lochmatter et al., 2008). This

software is an open source tool developed at the EPFL

for the tracking of robots, animals and objects using a

camera.

The remainder of the paper is organized as fol-

lows: Section 2 presents and describes brieﬂy the the-

oretical aspect related to the control of wheeled mo-

bile robots. Section 3 describes the platform of the

Moway robots. Section 4 describes the platform for

the Khepera IV robots. Section 5 makes a compari-

son between these two platforms. Finally, Section 6

presents the main conclusion and future work.

Fabregas, E., Farias, G., Peralta, E., Sanchéz, J. and Dormido, S.

Two Mobile Robots Platforms for Experimentation: Comparison and Synthesis.

DOI: 10.5220/0006469004390446

In Proceedings of the 14th International Conference on Informatics in Control, Automation and Robotics (ICINCO 2017) - Volume 2, pages 439-446

ISBN: Not Available

439

2 CONTROL EXPERIMENTS

Both robots used in the platforms are based on the dif-

ferential model. In this model the movement is based

on two separately driven wheels placed on either side

of the robot body. It can thus change its direction by

varying the relative rate of rotation of its wheels. The

linear and angular velocities (ν, ω) are obtained from

the differential model of a wheeled robot. While the

kinematic model of the robot (Eq. 1) can be obtained

in cartesian coordinates (Chwa et al., 2006), where θ

is the heading direction angle of the robot and (x

)

is the current position of the robot.







˙x

= ν cosθ

˙y

= ν sin θ

θ = ω

(1)

In this section two control problems with mobile

robots, based on the feedback control loop scheme

are described: 1) Position control, and 2) Leader-

followers formation control.

2.1 Position Control

This problem is titled position control or point sta-

bilization of a differential wheeled mobile robot. Its

objective is to drive the robot from the current posi-

tion C(x

, y

) and orientation (θ) to the target point

, y

), as it is shown in Figure 1. R is the distance

from the center between the wheels to the ICC (In-

stantaneous Center of Curvature). This problem has

been widely studied mainly due to the designing of

the control law, under nonholonomic constraints, in-

troduces challenging control problems from the aca-

demic and research points of view (K

uhne et al.,

2005). In order to achieve the control objective, the

distance (d) and the angle (α) between the points C

and T

are calculated with Eq. 2 and 3.

Figure 1: Position control problem.

d =

− y

)

+ (x

− x

)

(2)

α = tan

−1



− y

− x



(3)

Figure 2 shows the control blocks diagram of this

problem. The robot tries to minimize the orientation

error, θ

= α − θ, and at the same time, to reduce the

distance to the target point (d = 0). Eq. 2 and 3 are

implemented in the block Compute; by using as ref-

erence the target point (T

) and the current position

of the robot (C). These two values and the orienta-

tion θ are used by the Control Law block to obtain the

control signals (velocities).

Compute

Control Law

Wheels

Robot

Controller

Position Sensor

x, y, θ

Figure 2: Diagram of the position control problem.

Equations 4 and 5 represent the implementation

of the Control Law block. Where ν

max

is the maxi-

mum linear velocity, K

is the radius of a docking area

(around the target point) and ω

max

is the maximum

angular velocity of the robot (Villela et al., 2004).

ν =

(

max

i f

> K



max



i f

≤ K

(4)

ω = ω

max

sin(θ

) (5)

2.2 Leader-Followers Formation

In this experiment one robot is deﬁned as leader and

the rest of them as followers. All robots implement

the position control experiment. But in the case of the

followers robots, they use the position of the leader as

target point to reach the formation around it. The fol-

lowers implement Equations 6 and 7 where the point

, y

) represents the distance from the master to

the corresponding slave in the formation.

− y

)

+ (x

− x

)

(6)

α = tan

−1



− y

− x



(7)

During the experiment the formation can be lose

because the leader does not take into account the

formation (non-cooperative approach). If the leader

robot take into account the position of the followers

ICINCO 2017 - 14th International Conference on Informatics in Control, Automation and Robotics

440

into the formation then the formation is maintained

during the displacement (cooperative approach). To

do it the leader robot calculates its linear velocity us-

ing its position error and the error of the formation as

is shown in Eq. 8 (Lawton et al., 2003).

(t) =

∑

n=1

(t) (8)

Where E

is the total error between the current po-

sition of the followers (N) and the desired formation

pattern (E

). The velocity of the leader depends on

its own position error (E

) proportionally (through a

gain K

) and the formation error (E

) through a gain

, which decide the inﬂuence of the formation error

in the speed of the leader.

(t) = K

(t)− K

(t) (9)

3 Moway PLATFORM

This platform has been titled RFCP (Robots Forma-

tion Control Platform). It consists of two main parts:

the RFCSIM (Fabregas et al., 2014) which is a simu-

lator for virtual experiments with Moway robots and

the RFCEXP (Fabregas et al., 2015) which is an ex-

perimental environment for laboratory practices.

3.1 RFCSIM

The RFCSIM is a simulator in 2D that has been de-

veloped using EJS. Simulations are structured by EJS

into three categories: Description, Model and View.

The Model is divided into sections (Variables, Initial-

ization, Evolution, Fixed relations, Custom and Ele-

ments). All of these sections can contain Java code

used in different parts of the simulation in run-time.

The Variables section contains all the variables used

in the simulation. The Initialization contains some

lines of code necessary to initialize parameters of the

simulation; Evolution is the most important section

because it includes the code that will be executed at

each step of the simulation, such as the ordinary dif-

ferential equations of the model. The Fixed relations

panel allows deﬁning the constraints of the model, the

control algorithm or the view.

In the Evolution some parameters of the simula-

tion can be established: number of frames per second,

time increment and the method to solve the ordinary

differential equations. On the other hand, the View

(Fig. 3) allows creating the GUI that includes visual-

ization, user interaction, and simulation control. The

View elements can be chosen from a set of predeﬁned

components to build a tree-like structure. All of these

visual components are interconnected between them,

with the variables and the Java code of the Model.

Figure 3: EJS View of RFCSIM.

The main window of RFCSIM is divided into ﬁve

main panels (see Fig. 4). With panel No.1 users can

save and load experiments, get some help, manage the

execution of the simulation (play, pause and step), se-

lect the formation (free, circular, line) and establish

the number of robots and obstacles for the experi-

ments. Panel No. 2 shows the scenario of the ex-

periments with the obstacles, the robots and a trace

of the trajectory followed by each robot. Users can

change the robots and obstacles positions by dragging

and dropping them during an experiment. The effect

of these actions is different if the formation mode is

free or other option is selected. In the ﬁrst case, the

user can set a new formation by dragging and drop-

ping the robots. In other cases this acts over the robots

as a disturbance.

Figure 4: RFCSIM main window.

Two Mobile Robots Platforms for Experimentation: Comparison and Synthesis

441

Panel No. 3 is to deﬁne the properties of the se-

lected obstacle avoidance algorithm (VFF, VFH

∗

VFH

). Panel No.4 is to deﬁne physical properties of

the robots (minimum turning radius and control law)

and obstacles (size, velocity and security margin size

around them). Panel No. 5 is a tabbed panel with two

tabs. In the ﬁrst tab two graphics are shown: the po-

sition of the robots and the control law signals and a

polar histogram of the master robot.

3.2 RFCEXP

RFCEXP has been developed to carry out posi-

tion control experiments with Moway robots (Innova,

2012) taking into account their properties and fea-

tures. Moway is an small wheeled mobile robot based

on a differential model.

To implement this kind of experiments, the robots

need to know their absolute positions and to com-

municate between them. The setup is composed of

ﬁve hardware and three software components that are

deeply related. Fig. 5 shows the architecture and the

relations between these elements.

Figure 5: Architecture of the experimental environment.

A Personal Computer (PC) runs the software com-

ponents and has a CCD camera connected via a

FireWire port. The camera is installed on the ceiling

of the laboratory and is in charge of obtaining live im-

ages of the experiments. These images are processed

by SwisTrack. This application computes the absolute

positions of each robot and builds a data packet with

this information. This packet is sent via TCP/IP port

to the Gateway Module.

The Gateway Module is an application developed

using Visual C#. This program performs three main

tasks: 1) It processes the packet received from Swis-

Track; 2) It sends the information to the correspond-

ing robot using the RF USB Module, and 3) It receives

and responds the request from the Monitor Module.

The RF USB Module is a hardware component

of the Moway robot for the communication between

them and the PC using RF (Radio-Frequency).

The Monitor Module is a software application de-

veloped using EJS. Its main purpose is the interaction

between users and robots by visualizing the behavior

of the experiment using the video streaming of an IP

camera. The users can also send information to the

robots. For example, they can set the initial position

of the robots at the beginning of an experiment, or

send the reference to a robot during an experiment.

Figure 6: Experiment of robots formation control.

The most important components of this setup are

the Moway robots (No. 7). They are autonomous

small programmable robots designed mainly to per-

form practical applications, teaching robotics, tech-

nology, electronics, and control. They represent a

complete low-cost learning solution that allows users

to program an electronic control through simple and

intuitive software. The main components of these

robots are: two independent servo motors, a light

sensor, a temperature sensor, two infrared line sen-

sors, four LED diodes, a three-axis accelerometer

and a wireless module for communication by radio-

frequency. All these peripherals are connected to the

micro-controller that governs the robot.

Fig. 6 shows an experience with the experimental

ICINCO 2017 - 14th International Conference on Informatics in Control, Automation and Robotics

442

environment (top image is from a video streaming and

bottom image is form the Monitor Module). In this

case the with 1 robots as master and 5 robots as slaves

making a circular formation around him. The slaves

have to maintain the constant the their positions in re-

spect to the master’s position. Note that in this kind

of experiments, robots need to communicate between

them because the slaves need to know the position of

the master (as reference) to make the formation.

4 Khepera IV PLATFORM

This platform has been titled KH4P (Khepera IV Plat-

form). It consists of two main parts: the KH4VREP

(Peralta et al., 2016) which is a model of the Khepera

IV robot for V-REP simulator and KH4EXP which is

an experimental environment for laboratory practices

with the Khepera IV robot.

4.1 KH4VREP Library

In this case each visual component of the Khepera IV

robot (case, base, wheels, among others) was care-

fully modeled in 3D using Autodesk Inventor. The

obtained prototype was imported into V-REP as .stl

format. As ﬁnal step, the model was assembled in V-

REP. Most sensors of the robot were designed based

on the V-REP Khepera III model. In the case of the

camera (which is not included in previous Khepera

family version) was conﬁgured based on the existing

camera of V-REP library. The integration of the model

into V-REP allows the interaction with a large number

of examples, models of robots, sensors and actuators

that comes with it.

Figure 7: Khepera IV Library example.

To create an experiment is as simple as dragging

and dropping the robot model into the workspace and

program the script associated to the robot. When the

model is added to the virtual world of V-REP, it can

interact with the included models during the running

time. Also other new models can be designed and

added to V-REP to implement customized simulation

experiments. Figure 7 shows the library running an

example of a position control experiment.

4.2 KH4EXP

As in the previous approach, the main purpose of this

new platform is also to perform control experiments

with real mobile robots. In this case, the mobile robot

is a Khepera IV (KTeam, 2015). This is the fourth

generation of the Khepera robots family of the Swiss

company K-TEAM.

Khepera IV is a wheeled mobile robot that has

been designed for indoor pedagogical purposes and

it brings numerous features, for example, a colour

camera, Wi-Fi and Bluetooth communications, an ac-

celerometer, a gyroscope, improved odometry and

precision, an array of 8 infrared sensors for obstacle

detection, 5 ultrasonic sensors for long range object

detection, 2 very high quality DC motors and a Linux

operating system core.

In this implementation, the robot is connected to

a Wi-Fi router that allows wireless communication of

the robot with other components of the platform: the

IPS and the Monitor Module. Almost any existing

C/C++ library can be easily ported on the Khepera

IV, allowing the development of portable embedded

algorithms and applications.

As is known the GPS does not work on indoors

environments. That is why it is necessary the imple-

mentation of a positioning system to develop position

control experiments. As in the previous approach, a

PC has been used as the “brain” of the system, but in

this case with Linux. The PC is in charge of ruining

the software components of the system (SwisTrack)

and the Monitor Module.

A PlayStation 3 (PS3) USB camera (ﬁxed to the

ceiling) is connected via USB to the PC. The images

of this camera are processed to obtain the position of

the robot. Figure 8 shows the architecture of the plat-

form with all software and hardware components and

their interactions. Note that the red line encloses the

components of the positioning system and the green

line encloses the components of the Monitor Module.

Monitor Module has been developed in Easy Java

Simulations (EJS) and it allows the interaction be-

tween users and the robot. Its GUI shows the stream-

ing of the IP camera. By clicking on the image the

target point for the position control of the robot can

be set. Monitor Module is also in charge of two

other tasks: a) the communication with SwisTrack via

TCP/IP client at port 30001 (labelled as 2 in Fig. 8);

Two Mobile Robots Platforms for Experimentation: Comparison and Synthesis

443

Figure 8: Platform architecture.

and b) the communication with the robot using a wire-

less router via TCP/IP client through port 1291 (la-

belled as 3 in Fig. 8).

Figure 9 shows shows a sequence of images of the

control position experiment for eight different initial

positions and orientations. In all cases the target point

is T

(0;0). As can be seen, due to the initial orienta-

tion and position of the robot, each experiment de-

scribes a different trajectory.

Figure 9: Image sequence of the Position Control experi-

ments.

4.3 Advanced Proposed Experiments

The platform is a ready to use tool that allows the im-

plementation of different experiments to study some

interesting problems of mobile robots. These experi-

ments can include sensing and movement tasks for a

single robot or cooperation in a multi-robot scenario.

Some of the experiments that could be implemented

with the developed platform are the following:

• Obstacle avoidance: Using the proximity sensors

and their location on the robot, other algorithms

of obstacle detection and avoidance can be imple-

mented (Yang et al., 2006).

• Occupancy Grid Mapping: Using the proximity

sensors of the robot, an occupancy grid of the en-

vironment can be built and stored in memory. This

experiment can be implemented using the position

control experiment as a basis or with odometry us-

ing the encoders of the robot to know its position

during the navigation (Thrun et al., 2000).

• Multi-sensors fusion: Both types of proximity

sensors can be used (infrared and ultrasonic) to

get a better certainty of the presence of the obsta-

cles in the environment.

• Multi-robots: Communications between the two

platforms to perform multi-agents experiments

with different kind of robots.

• Pursuer-Evader Games: In this type of problem,

the robots compete with each other to pursue their

own objectives like in (Casini et al., 2014).

5 PLATFORMS COMPARISON

This section presents a comparison between the two

platforms from different points of view: usability,

hardware/software components, costs, versatility to

implement new experiments, wireless communica-

tions reliability, advantages and disadvantages of use.

Since the two platforms have similar architectures,

the comparison must be focused for example, in the

robots (processing capabilities), the kind of experi-

ments that can be performed, the ease to incorporate

new robots to the work-space and the communica-

tions between the robots.

In the simulation part it is very evident that the

use of V-REP is a big advantage with respect to EJS.

Once the model is added to the virtual world, it can

interact with a complete list of robots models that V-

ICINCO 2017 - 14th International Conference on Informatics in Control, Automation and Robotics

444

Table 1: Platforms comparison.

Moway platform Khepera IV platform

Simulator RFCSIM (2D) V-REP (3D)

Simulator Programming Java Lua

Other models No Yes, V-REP models

Experiments complexity Low-medium Low-high

Robot Model Differential (Wheeled) Differential (Wheeled)

Robot Programming Ansi C C

Wireless Communications Radio Frequency Wi-Fi

Data Packet 8 Bytes 32 Bytes

Free Software Yes Yes

Multi-Robots Yes Yes

Sensors Low quality High quality

Processor PIC18F87J5 (4M Hz) ARM Cortex-A8 (800 MHz)

Internal Memory 50 MB 4 GB

Battery 2h 5h

Code upload USB wire Wireless

Price 150e 3500e

REP includes. Maybe a good idea can be for the near

future the development of the Moway robot model for

V-REP. In this case the main drawback is that the sim-

ulation will not embedded in a web page to be used it

through Internet. Besides, EJS ﬁles can be embed-

ded in a web browser because the simulation can be

exported as JavaScript code. This is a very nice ad-

vantage with respect to the rest of well known robot

simulators.

In both platforms the most important component

are the robots. The experiments that can be carried out

with the platforms depend meanly on four elements:

1) Sensors of the robot, their quality and precision;

2) The level of data processing of the robot on-board;

3) The wireless communications capabilities; and 4)

Memory for storing data.

Taking into account that, Moway robots are low-

cost devices and Khepera robots are very power full

machines, but very expensive. The main advan-

tage/disadvantage of both robots are the following:

• Moway robots are a cheap solution that allows to

implement experiments of low and medium level

complexity, for example: line following, obstacles

avoidance, sound detection, etc...

• Khepera robots are a complete solution that al-

lows to implement experiments from low to high

level complexity including the two mentioned be-

fore and other cooperation experiments because

the communication is highly reliable.

Another detail in this comparison is the usability

of the robots during the development and implemen-

tation of the experiments. To load the program to the

Moway it is necessary to connect it to the PC with a

USB cable. While for the Khepera robot, the code can

be loaded trough the Wi-Fi connection, which means

it is not necessary to connect it to the PC with a cable.

This is an important detail because in this kind of ex-

periment it is always needed to reprogram (upload the

code to) the robot in order to test the developments.

The processing capabilities of the robots is an-

other important issue in this kind of platforms. De-

pending on the experiment the differences can be

very signiﬁcant when performing complex mathemat-

ics operation and calculation. In many cases the com-

putation is very intensive, thus this feature is normally

desired.

Other important point to be considered is the com-

munications capabilities of the robots. The RF mod-

ule of the Moway robots sometimes loses the commu-

nication with the PC due to the noise and interference

of other wireless communications that work in near

frequencies. It is important to take this into account

because the designer can think that the development is

not working properly due to the algorithm, but maybe

it is due to the communication lose. Such issue is very

limited in the case of Khepera communication.

Some experiments do not need that robots ex-

change information between them. But in many

cases, such as in formation control experiments (co-

operative approach), robots need to exchange infor-

mation on each iteration. If the capabilities of com-

munication are not enough, maybe the needed data

has to be sent twice. This can have a very strong in-

ﬂuence in the performance of the experiment. Table 1

shows some elements of both platforms to summarize

the comparison between the two platforms.

Two Mobile Robots Platforms for Experimentation: Comparison and Synthesis

445

6 CONCLUSIONS

This paper presents two platforms developed to carry

out experiments with mobile robots for pedagogical

and research purposes. Both platforms are divided

into two parts: 1) A virtual environment; and 2) An

experimental environment.

The virtual environment of the Moway robots has

been developed in EJS. The result is a perfect 2D sce-

nario to test different mobile robots position control

experiments taking into account only the most impor-

tant issue: the design of the control algorithm. In the

Khepera IV platform, the virtual environment V-REP

simulator has been used.

The experimental environment is similar in both

cases. A camera captures an overhead image of the

work-space where the robots are. Then using Swis-

Track the absolute position of the robots are calcu-

lated and sent to each robot using a wireless commu-

nication. In both platforms the result is a ready-to-use

environment that allows to perform quickly control

experiments with mobile robots. To test the platforms

some experiments have been designed and developed:

position control and leader-followers formation con-

trol experiments.

The comparison shows that the most important

component in this kind of platform is the robot, be-

cause these platforms are developed to carry out ex-

periments with them. Such experiments depend on

the sensors and characteristics of the robots. For

example: the wireless communications between the

robots and the PC.

ACKNOWLEDGEMENTS

This work has been funded by the Spanish Ministry

of Economy and Competitiveness under the Project

DPI2014-55932-C2-2-R and the Chilean Ministry of

Education under the Project FONDECYT 1161584.

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