LEADER-FOLLOWER FORMATION CONTROL OF

NON-HOLONOMIC ROBOTS IN A REMOTE LABORATORY

Daniel Neamtu, Bart Wyns, Robin De Keyser and Clara Ionescu

Department of Electrical Energy, Systems and Automation, Ghent University, Technologiepark 913, Zwijnaarde, Belgium

Keywords:

Remote laboratory, Mobile robots, Formation control, Distance education.

Abstract:

This paper presents a remote laboratory for leader-follower formation control. The client-server architecture

of the remote laboratory is based on Matlab and JIM at the server’s side, and a Java applet created using Easy

Java Simulations at the client’s side. The implementation of the remote laboratory is described in detail and

the educational value is outlined by presenting some experimental results for formation control of two mobile

robots.

1 INTRODUCTION

Nowadays technology is evolving at an incredible

pace, providing us with possibilities that a few

decades ago were unimaginable. The development

of communication and information technologies has

completely changed the speed and penetration of in-

formation in today’s society. The teaching activity in

general has a lot to gain from the use of these new

technologies. Remote and virtual laboratories are be-

coming increasingly popular. Remote laboratories, as

compared to the classic on site instruction, present

several advantages (Dormido, 2004): i) continuous

availability of the laboratory for experimentation, ii)

there is no need for the students to travel to the univer-

sity’s site in order to perform the experiments, iii) op-

timal exploitation of the resources, iv) easy access to

different types of experiments. A very broad range of

applications can make the object of remote laborato-

ries, with some notable exceptions for example in the

chemistry ﬁeld where safety requirements can pro-

hibit the use of a remote laboratory (Dormido, 2004).

In particular, remote laboratories are becoming very

popular in the ﬁeld of control engineering mainly due

to the interactivity that they provide to the distance

teaching process. A few examples of remote labo-

ratories designed for performing control experiments

are given in (Vargas et al., 2009; Fabregas et al., 2009;

Farias et al., 2010), to mention just a few. These re-

mote laboratories are meant to remotely control a sin-

gle process (water tank, ball and hoop, DC motor etc.)

allowing the remote user to change the parameters of

the controller, visualizing incoming data and enable a

real-life view of the process itself.

The ﬁelds of robotics receives very much inter-

est both from the academic and industrial communi-

ties worldwide, which means that proper education in

this ﬁeld becomes more and more important (Potkon-

jak et al., 2010). Building a remote laboratory for

robotic experiments is a complex task due to the in-

terdisciplinary character of this application. A few

examples of remote laboratories with the purpose to

experiment with robotic applications are presented in

(

Safari

c et al., 2005; Casini et al., 2009; Sayouti et al.,

2010).

In the remote laboratory presented in this paper

the ﬁnal aim is to remotely control a group of mobile

robots so that they move in a leader-follower forma-

tion on a predeﬁned trajectory.

The proposed implementation is based on Matlab

and Easy Java Simulations (EJS) (Esquembre, 2004).

EJS is a free open-source tool for easily creating sim-

ulations in Java, and targets students, teachers and re-

searchers who want to quickly create a graphical sim-

ulation. EJS was originally designed to be used by

students for interactive learning under the supervision

of educators with little programming experience. In

this implementation of a remote lab, the graphical in-

terface and the computational engine are separated.

The graphical interface was created using EJS and is

an applet that runs in the user’s browser.

Matlab is the most commonly used program in

teaching control engineering. In our remote labora-

tory implementation, the computational engine is rep-

485

Neamtu D., Wyns B., De Keyser R. and Ionescu C..

LEADER-FOLLOWER FORMATION CONTROL OF NON-HOLONOMIC ROBOTS IN A REMOTE LABORATORY.

DOI: 10.5220/0003476904850490

In Proceedings of the 3rd International Conference on Computer Supported Education (UeL-2011), pages 485-490

ISBN: 978-989-8425-50-8

 2011 SCITEPRESS (Science and Technology Publications, Lda.)

resented by Matlab, which runs at the server’s side.

In the next section a description of the components

that constitute the remote lab is given. In section 3 we

discuss the application of the remote lab for control-

ling a formation of robots and in the last section some

conclusions are drawn and the planned future work is

outlined.

2 COMPONENTS OF THE

REMOTE LAB

2.1 General Overview

The most popular architecture used for remote lab

implementations is client-server. The client runs on

the remote user’s computer, who can access the func-

tions of the remote lab through a graphical user inter-

face. The server, which runs at the University’s site,

should be transparent for the user and insure the con-

nection with the process. The client-server connec-

tion is made using the TCP/IP protocol, over Internet,

as depicted in ﬁgure 1.

Figure 1: Client-server architecture.

Information is sent bidirectionally between the

client and the server. The client sends commands to

the server which are further sent to the process. From

the server to the client comes data acquired from the

process, real-time images of the experiment and dif-

ferent messages: the process is not connected to the

server, changes in the state of the process, alarms

when something goes wrong. Due to the high vol-

ume of data sent from the server to the client, a high

speed internet connection is necessary. The camera

has a separate internet connection so that the video is

not delayed by the data coming from the process.

2.2 Hardware

While at the client’s side a single PC with Internet

connection is sufﬁcient, at the server’s side there are

several hardware devices, as depicted 2. In our imple-

mentation, the server itself runs on a dedicated com-

puter with permanent Internet connection. The com-

puter used is powerful enough to efﬁciently run all the

required software (Matlab, Apache Server, JIM) and

it has enough memory to store the data coming from

the process. It has been equipped with two network

cards: one Ethernet card used for connecting to the

Internet and a wireless card used to connect to a local

WiFi network.

Figure 2: Remote lab hardware components.

(a) Surveyor SRV-1. (b) SRV1 Blackﬁn camera.

Figure 3: Mobile robot used in the remote lab.

The remote user can continuously monitor the

controlled process by looking at images sent from a

network camera via a separate internet connection, as

shown in ﬁgure 2. Due to the nature of this applica-

tion, namely mobile robots in motion, the camera has

to cover a large area. For this reason, a PTZ (Pan-Tilt-

Zoom) camera was chosen such that the user is able

to move the view of the camera to the view of interest.

The process, in our case a group of non-holonomic

robots, is connected to the server using wireless

communication through a local WiFi network. The

Surveyor-SRV1

, shown in ﬁgure 3, is a tracked mo-

bile robot equipped with a 500 MHz microprocessor,

an on-board camera and WiFi communication. An

expansion board is available for the robot with tilt

sensors, a compass and GPS receiver. In the current

experiments, the controlled signal is the duty ratio

of the PWM signal sent to the motors and the out-

put of the process is the distance between two robots

measured using the on-board camera. The camera on

the robots supports several resolutions for the images,

however for our experiments it was chosen a resolu-

tion of 320 × 240 pixels, as a trade-off between com-

putational time and measurement accuracy. The cam-

http://www.surveyor.com

CSEDU 2011 - 3rd International Conference on Computer Supported Education

486

era uses YUV color representation, where Y repre-

sents the light intensity and the U and V are chroma

components.

Surveyor-SRV1 is a differentially driven robot.

The lack of wheel encoders makes the speed of the

robot run in open loop. This aspect makes the control

task more difﬁcult particularly due to the nonlineari-

ties of the motors and the offset in angular speed be-

tween the right wheel and the left wheel. Due to this

latter aspect, lateral control of the robot is compul-

sory for maintaining the formation. The speed of the

robot is in the range 20 cm/s - 40 cm/s with a nonlin-

ear characteristic, containing a dead-zone until 20%

of the total input range.

2.3 Software

The client-server software architecture of the remote

lab is shown in ﬁgure 4. The communication be-

tween the client and the server is accomplished us-

ing a TCP/IP Internet connection. On the other hand,

communication between the server PC and the mobile

robots is accomplished using TCP/IP communication

through a local network.

Figure 4: Remote lab software components.

The software requirements for the end-user are

minimal, a Java enabled web browser, which insures

the ease of use of the remote laboratory but also porta-

bility. The remote user downloads a Java applet which

displays the graphical user interface, shown in ﬁgure

5. The Java applet was generated using Easy Java

Simulations (EJS) (Esquembre, 2004). This applet

provides a user-friendly graphical user interface for

the user to access the functionalities of the remote

lab. First of all, there are live images from the ex-

periment’s site in the top left side of the GUI. The

buttons and the slider adjacent to the image of the

process enable the user to control the orientation and

the zoom of the PTZ network camera. Underneath

this, there are buttons to manually control the robots,

connect/disconnect the robots to the server, start/stop

automatic control. The right side of the GUI is for dis-

playing the data measured by the robots in the forma-

tion which consists of relative distance measurements

and the values sent to the left and right motors of the

robots. The values from the plots can be saved using

a tool provided by EJS. Also on the right side, one

of the panels is dedicated to experimenting with im-

age processing functions available on the robot: color

segmentation, edge detection and horizon detection.

Figure 5: Graphical user interface displayed in the Java ap-

plet.

A diagram of the programs that presents the soft-

ware components of the remote laboratory is shown in

ﬁgure 4. JIM

(Java-Internet-Matlab) server is a free

software tool written in Java that allows communica-

tion between a remote user and a Matlab server. The

connection between the remote applet and JIM is im-

plemented using a TCP/IP connection. JIM is able to

communicate with Matlab using the functions deﬁned

in the JMatlink library (M

uller and Waller, 1999).

Matlab has been chosen to be incorporated in the

structure of the remote lab since it is the tool most

widely used in the control engineering world. Matlab

provides state of the art computational capabilities.

Matlab’s core computational capabilities are extended

through several toolboxes. Information between the

ﬁrmware on the robots and the server is exchanged by

making use of the Instrument Control Toolbox

. Sev-

eral TCP/IP connections are made in Matlab to the

mobile robots. The commands issued by the user us-

ing the GUI are sent to Matlab which translates these

commands into characters that can be processed by

the ﬁrmware on the robots. The role of Matlab is also

to receive the data coming from the robots and make it

available to the remote applet through the transparent

link provided by JIM server.

The camera is running a web server that can re-

ceive commands from a remote user. The user can

control the PTZ network camera from the GUI. These

actions are translated into HTTP queries which are

sent to the web server on the camera. The HTTP

http://lab.dia.uned.es/rmatlab/

http://www.mathworks.com/products/instrument/

LEADER-FOLLOWER FORMATION CONTROL OF NON-HOLONOMIC ROBOTS IN A REMOTE LABORATORY

487

queries are translated into actions for the servos of the

camera – pan and tilt – and for the lens – zoom action.

The ﬁrmware running on the robots is open-source

and can be easily modiﬁed using C programming

language. Some of the functionalities available are:

real-time timing, image acquisition, image process-

ing – using color segmentation and edge detection,

integer number computations, ﬂoating point compu-

tations using a library, control of the motors using

PWM signals etc. The tracking algorithm which con-

sists of image processing for estimating the distance

and computing the control value to be sent to the mo-

tors takes 70 ms. This value represents the sampling

time of the process. All the robots have a static IP as-

signed so that they are easy to identify in the network.

3 CONTROL EXPERIMENT

A leader-follower formation assumes that there exists

one or more leaders in the formation and the other

robots, the followers, copy the actions of the leader. In

this work, a single leader, column formation is used.

This formation is similar to the cars on one lane of a

highway, where cars follow each others and maintain

a safe distance. Similar implementations of formation

control of mobile robots are described in (Anderson

et al., 2006) and (Klan

car et al., 2009).

Figure 6: Leader-follower formation.

In a leader-follower formation, the followers

should maintain a constant distance and a constant

relative angle with respect to the robot in front. For

the experiments, we set the distance reference to d =

30 cm and the angle reference to θ = 0

◦

(see ﬁgure 6).

Relative distance and relative angle are measured

using image processing on images taken by the on-

board camera. In order to distinguish the robots from

the environment, a rectangular red marker with the di-

mensions 8.1cm × 3.6cm was attached to the back of

the robots. The follower robot captures frames from

the on-board camera and using adaptive color seg-

mentation, the red marker is isolated in the image.

The projection of the marker in the plane of the

image is computed in pixels. The values of interest

are the height of the blob and the position of blob on

the horizontal axis. A relationship between the height

Figure 7: Measured distance - height characteristic.

of the blob and the real distance was determined ex-

perimentally, the result is shown in ﬁgure 7. The re-

gion of the characteristic depicted with red is almost

linear, between 20 cm and 60 cm. On this region a 3

order polynomial was ﬁtted, with as input the height

of the marker in the image measured in pixels, and

output the distance d between the robots measured in

centimeters:

d = −0.0004 · h

+ 0.0717 · h

−

−4.53 · h

+ 125.16 (1)

The accuracy of this measurement is between 1-

4 cm, depending on the focus of the camera and the

distance between the robots.

the position of the marker on the horizontal axis

of the image is considered in order to estimate the rel-

ative orientation between the robots. Taking into con-

sideration that the resolution of the image is 320 ×

240, a 0

◦

relative orientation is achieved when the

center of the marker in the image, relative to the hori-

zontal axis, is equal to 160 pixels. This measurement

cannot exceed the ﬁeld of view of the camera which is

◦

in total. This measurement procedure is affected

by errors when the marker is only partially visible in

the image, either due to changing light or if the ori-

entation angle between the robots exceeds the ﬁeld of

view of the follower’s camera.

The control algorithm is implemented on the mi-

croprocessor of each robot, thus we have a decentral-

ized formation control. So far, no direct communi-

cation among robots is possible. Communication can

be implemented using a central communication point

through the server, which would have the task to for-

ward messages from one robot to the other.

The goal is to have a good longitudinal control on

the robots so that the leader-follower formation is pre-

served. On the other hand, lateral control is also nec-

essary for maintaining the formation and the marker

CSEDU 2011 - 3rd International Conference on Computer Supported Education

488

Figure 8: Control structure used for tracking.

in the ﬁeld of view of the follower. A drawback of the

Surveyor SRV-1 is the lack of wheel encoders so all

the robots present an offset in the rotational speed of

the left and right tracks. This offset means that for the

same PWM values sent to both the left and right side,

the robot will not drive straight as it should. In order

to solve this issue, a second controller was added for

the lateral dynamics.

The structure of the controller is presented in ﬁg-

ure 8. The longitudinal controller is a PID. The refer-

ence distance is set constant d

re f

= 30 cm. The mea-

sured distance is continuously disturbed by the move-

ment of the robot in front. This longitudinal distur-

bance is denoted D

lon

in ﬁgure 8. Due to the offset

of the motors and the movement of the leader, there

is a disturbance D

lat

on the lateral dynamics of the

system. A PI controller receives the error between

the reference angle α

re f

= 0 and the measured angle

α. The commands to the motors of the robots are ob-

tained using the longitudinal and lateral control, ac-

cording to the formula:

= u

lon

− u

lat

, V

= u

lon

+ u

lat

(2)

where V

and V

are the PWM duty cycles sent to the

left and right motors of the differentially driven robot;

lon

and u

lat

are the outputs of the longitudinal PID

controller and of the lateral PI controller.

Figure 9: Tracking result for one leader and one follower.

The proposed control strategy shows good per-

formance. In ﬁgure 9 it is presented the result for

tracking of one robot using the proposed control strat-

egy. The formation of two robots was running along a

straight line, with the leader following a colored line

on the ﬂoor. After a transient of 4 s in the beginning,

the follower keeps a constant distance with respect to

the leader in front.

In order to decrease the ﬂoor space necessary for

the remote laboratory and to make it easier for the re-

mote user to supervise the experiment, an ellipsoidal

colored track of length 225 cm and at each end two

semicircles with diameters of 176 cm was put on the

ﬂoor. The leader of the platoon follows the colored

track while the follower robots maintain the line for-

mation. The task of the followers it is more difﬁcult

when the path is not straight. Turning of the robots

can cause the formation to be broken or can induce

oscillations in the lateral control that will propagate

in the entire formation.

4 CONCLUDING REMARKS

This paper presented a remote lab for robotic applica-

tions. The remote laboratory was implemented using

Matlab and EJS connection supported by JIM Server.

The educational value of this remote lab comes from

the fact that students will be able to experiment with

this setup and tune the PID control.

This paper shows once again the added value that

new technologies bring to the teaching process. Ex-

perimentation on the developed laboratory provides

a fundamental educational feature: students can ob-

serve on-the-ﬂy the resulting dynamics and be aware

of some physical phenomena that are less obvious,

difﬁcult to explain from just a theoretical point of

view.

Planned future work includes decreasing the min-

imum speed of the robots by changing the mechani-

cal reduction of the motors, so that they are able to

maintain the formation in a larger number on the el-

lipsoidal track on the ﬂoor. There are also plans of en-

hancing the functionality of the remote laboratory by

adding more options to the graphical user interface:

controller parameter changing, select between mul-

tiple controllers, perform identiﬁcation experiments,

auto-tunning.

ACKNOWLEDGEMENTS

The authors would like to thank to KCO for funding

this project.

Also, the authors express their gratitude to Enersto

LEADER-FOLLOWER FORMATION CONTROL OF NON-HOLONOMIC ROBOTS IN A REMOTE LABORATORY

489

Fabregas Acosta from the UNED University, Madrid,

Spain.

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