Robot Soccer is a rich domain for the study in artificial intelligence. Teams of players must work together in order to put the ball in the opposing goal. Learning is essential in this task since the dynamics of the system can change as the opponents’ behaviours change. The players must be able to adapt to new situations. In this paper, we create a passing, avoiding obstacle and shooting strategy for robot soccer coordination. Based on a scenario in robot soccer, we stimulate a mini case study which involves two robots and ball.This research proposes coordination algorithm for robots collaboration in soccer game. The method is based on

role, act, and behaviour of the robots. The actions of each robot depend on the created situation. The simulation result shows its probability to be applied in the real robot soccer game

Abdullah, Siti Norul Huda Sheikh

Noordin , Md Jan

Omar, Khairuddin

Prabuwono, Anton Satria

Pratomo, Awang Hendrianto

Zakaria, Mohamad Shanudin

UPN (Universitas Pembangunan Nasional) Veteran Yogyakarta: Institutional Repository

itif cn  e Ci oc nS fl ea rn eo ni ct ea  2nr 0e 1t 1nI
ISC 2011
Proceeding of the International Conference on Advanced Science, 
Engineering and Information Technology 2011
Hotel Equatorial Bangi-Putrajaya, Malaysia, 14 - 15 January 2011
ISBN 978-983-42366-4-9
ISC 2011
International Conference on Advanced Science,
Engineering and Information Technology
ICASEIT 2011
Cutting Edge Sciences for Future Sustainability
Hotel Equatorial Bangi-Putrajaya, Malaysia, 14 - 15 January 2011
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Organized by 
Indonesian Students Association
Universiti Kebangsaan Malaysia
Proceeding of the
Coordination Algorithm for Multi Robot
Collaboration in Soccer Game
Awang Hendrianto Pratomo1, 2, Anton Satria Prabuwono1, Mohamad Shanudin Zakaria1,
Siti Norul Huda Sheikh Abdullah 1, Khairuddin Omar1, and Md Jan Noordin1
1)Centre for Artificial Intelligence Technology, Faculty of Information Science and Technology
Universiti Kebangsaan Malaysia, 43600 UKM Bangi, Selangor D.E., Malaysia.
Tel : +60 38921 6090
2) Department of Informatics Engineering, Faculty of Industrial Engineering, University Pembangunan Nasional
“Veteran” Yogyakarta, Jl. Babarsari No.2. Jogjakarta 55281, Indonesia
Tel : +62 274 485323
awang.upn@gmail.com, {msz, antonsatria, ko, mimi}@ftsm.ukm.my
Abstract - Robot Soccer is a rich domain for the study in artificial intelligence. Teams of players must work together in order to put
the ball in the opposing goal. Learning is essential in this task since the dynamics of the system can change as the opponents’
behaviours change. The players must be able to adapt to new situations. In this paper, we create a passing, avoiding obstacle and
shooting strategy for robot soccer coordination. Based on a scenario in robot soccer, we stimulate a mini case study which involves
two robots and ball.This research proposes coordination algorithm for robots collaboration in soccer game. The method is based on
role, act, and behaviour of the robots. The actions of each robot depend on the created situation. The simulation result shows its
probability to be applied in the real robot soccer game.
Keywords - Robot soccer strategy, obstacle avoidance, shooting strategy, passing strategy.
I. INTRODUCTION
Robot soccer is a game similar to football match with
only one significant difference: the players aren’t humans
but robots. Normally, the robots are miniature wheeled
mobile vehicles because of their simple mechanical
construction and control [1]. Each team consists of five
players; one of them is the goal keeper, two robots as
defender and two robots as striker. Robots must be fully
autonomous and controlled by the computer. The CCD
camera mounted overhead the field and connected to the
computer is used for gaining the information about the
position of individual players and the ball. The game
between two teams (each having its own camera and
computer) is running without the human intervention, with
the exception of foul or stalemate situation, when the game
is interrupted and a free kick or penalty kick is called. The
game is judged by the human referee.
Robot Soccer is a rich domain for the study in artificial
intelligence. The robots players must work together in order
to find the ball their own goals and create goals in the
opponent goal [2]. Learning is essential in this task since the
dynamics of the system can change as the opponent’s
behaviours change. The players must be able to adapt to new
situations. Not only must the robots players learn to adapt to
the behaviours of different opponents, but they must learn to
work together. Soon after beginning to play, novice soccer
players learn that they cannot do everything on their own:
they must work together as a team to winning the game.
However, before robots players can learn any collaborative
or adversarial techniques, they must first acquire some
low-level skills that allow them to manipulate the ball.
Basic skills for robot soccer strategy such as: dribbling
and controlling the ball though entirely individual in nature
are as critical to the development of a robot soccer player
such as passing and receiving passes, which are more
collaborative in nature. Several research studies have been
done to develop robots soccer strategy that can play
[RoboCup Research & Education] [2]. However, because of
the rich and dynamic condition of the environment in robot
232
soccer game, directly programming of the robots soccer
strategy to play soccer is impractical, if not impossible.
Therefore, the main focus has been shifted to treat the robots
as an intelligent agent that can learn how to play soccer
under with different environments and conditions [3].
The objective of our research which is to create
algorithm for coordination about two robots to passing and
moving with obstacle avoidance for shoot the ball into the
goal. Besides that, we need to set and adjust the coordinate
of the robot to make sure shooting properly. However, we
also need to synchronize the timing between two robots, the
purpose of the synchronize are make sure the robot shooting
the ball into the goal area, at the same time, another robot
moved with obstacle avoidance to the shoot the ball from the
goal into goal.
II. METHODOLOGY
A mobile robot, which is equipped with a camera
mounted overhead in the field, is sketched in the lower right
area of the image. The data image reads from an image-
processing module that must try to detect an object. The
object is analyzed and reconstructed after a successful
detection. In our research in Robot Soccer programming we
used Visual C++ for created dll strategy files.
Robot Soccer game is a demanding application for the
robots have a very fast and the entire thinking and decision
making. The process must be finished after a few
milliseconds. The intense time pressure is the one reason for
the centralized robot team organization with a computer for
processing the strategy [4].
The main problem is the definition of the behaviour of
football match, included opponents model and strategy.
MiroSot system usually uses hard coded sets of if-then rule
that prevent easy updates or changes. Robot soccer is fully
autonomous control structure, the planning and activities of
the robot in the team controlled by the computer systems. [5].
The control architecture of robot soccer implements a
process where simple task achieving behaviours are added as
required. Each process is behaviour producing in its own
strategy, although it may rely on the presence and operation
of players [6].
The role level in control architecture is related to who.
It refers to choose a role and area of manoeuvre in the
playground for each robot such as: defender, midfielder,
attacker, and goalkeeper. In the act level that related to what
issue, that refer to selected an appreciate action for each
team robot according to assigned the role. Such as: dribbling,
passing, shooting, blocking, etc. behaviour level is refer to
the issue of how. That is refers to condition checking for the
robot condition such as the process of the robot for moved
the robot with or without obstacle avoidance. The execution
level is refer to motion of the robot for execute that
condition [7]. The execution level refers to hardware control
for controlling the motor for the robots movements.
III. DISCUSSION
In our research the robot 2 (R2) has to pass the ball to
shooting area and then at the same time, the robot 1(R1) has
move with avoid opponent defender (RD) and move to the
R’1 position and shoot the ball to goal in shooting area. In
our data, 1 pixel represents 2.78 mm. Position and moving
path of the R1, the R2, and the RD are shown in Fig.1.
Fig 1: Position and moving path of the R1, R2, RD and R’1
Coding below is the source codes for the R1 robot and the
R2 robot. Fig.2 is the algorithms that explain how these
source codes works.
Fig 2: Algorithm passing of the R2 [8]
Alorithm 1 : The proposed passing algorithm
Input : Current robot positions and the ball position.
Output : Robot velocity .
Step 1 : Assume each robot position , R is the robot, the ball
as ܾ , and
Step 2 : Estimate the ball to the target position .
dx1 = x_t - x_b; (1)
dy1 = y_t - y_b; (2)
Step 3 : Calculate distance, from the robot to the ball
dx2 = x_b - robot->pos.x; (3)
dy2 = y_b - robot->pos.y; (4)
Step 4: Estimate the rotation angle of the ball to the target,
and rotation angle of the robot to the ball.
Calculate desired shooting angle
if (dx2 == 0 && dy2 == 0)
phi2 = 90;
else
phi2 = (int)(180. / PI *
atan2((double)(dy2),(double)(dx2)));(5)
233
Step 5 : Calculate the angle error as the following.
theta_d = 2 * phi2 - phi1; (6)
theta_e = theta_d - (int) robot->rotation;(7)
Step 6 : Set the kinematic value or propotional gain,
if (abs(theta_e) > 50)
Ka =0.16;
else if (abs(theta_e) > 40)
Ka =0.18;
else if (abs(theta_e) > 30)
Ka =0.2;
else if (abs(theta_e) > 20)
Ka =0.22;
else Ka =0.24;
Step 7 : Calculate robot velocity of the robot movement,
vl = (int) (Vc - Ka * (double) theta_e); (8)
vr = (int) (Vc + Ka * (double) theta_e); (9)
Step 8 : End.
Different algorithms for the R1 and R2 are built and run
simultaneously. Algorithm for the R2 is shown in Fig.2.
In this case, the R2 will be placed at bottom of the field,
as shown in Fig.1. The R1 will be placed at the top of the
field. An opponent defender will be placed in front of the R1
to block its way as shown in Fig.3.
Fig.4 shows the actual position of the robot 3 and the
desired position.
i. Some of the method needs to code or program it, to
make sure the robot shoots the ball into the desired
location.
ii. Set the current position of the ball and position of
the robot.
Position of the robot in X-axes and Y-axes as shown in the
following code:
double x1 = (&env->home [n])->pos.x; (10)
double y1 = (&env->home [n])->pos.y; (11)
The codes for passing the ball are shown in the following
Algorithm:
Input : Current possition of all the robots and the ball, and
the subsequent position of the robots.
Output : Robot velocity
Step 1 : Assume the distance of the robot to the obstacle,
length of the free area from the robot position, to the
obstacle position, the difference angle between the robots to
the obstacle and the angle of the robots.
Distance = ඥ(ܱ௫ − ݔ)ଶ + ( ݕ− ܱ௬)ଶ (12)
length = fabs( (ܱ௫ − ݔ)*sin(ߠௗ )+(ݕ− ܱ௬)*cos(ߠௗ ) )(13)
angle = atan2(ܱ௬ − ݕ , ܱ௫ − ݔ ) (14)
diff_angle = ߠௗ − angle (15)
where :
Distance = distance from obstacle to the robot
ܱ௫, ܱ௬ = Obstacle x, y coordinate
X, y = Robot x, y coordinate
ߠௗ = Robot angle
Step 2 : Predict the subsequent action based on the condition
of obstacle and target point, calculate the safety margin for
collision avoidance and the radius of the obstacle.
Step 3 : If the action prediction is ‘move and avoid’, we
calculate the distance from the centre gravity of the obstacle .
Step 4 : Calculate the radius of the robot and the relative
position to the obstacle.
Step 5 : Estimate the desired position of the robot, the
bearing or the orientation of the robot.
Tx = Bx – Dh . cos ( t ) (16)
Ty = By – Dh . sin ( t ) (17)
Where :
Tx, Ty is the shooting position.
Bx , By is the ball position.
Dh is the desired distance behind the ball.
t is an angle from the ball towards the desired direction (in
radians).
Step 6 : Calculate direction of the robot behind the ball for
moving towards a shooting position to the goal.
ඥ(ܤ௑ − ܴ௑)ଶ + (ܤ௒ − ܴ௒) > ܦ௙ (18)
or
| Ф2 – Ф1 | < 90º
Where :
Bx , By is the ball position.
Rx, Ry is the robot position.
Df is the desired distance behind the ball.
Ф2 is an angle of ball to the target point (TP).
Ф1 is an angle of robot to the ball.
Step 7 : Use algorithm 1 to calculate the velocity of the
robots.
Step 8 : End.
To avoid the obstacle, we used control statement to
control the different condition. For example when the robot
position reach the x-axes larger than 45 and if robot Y detect
obstacle then it will avoid clash with the obstacle.
Fig 3: Position of the R1, R2 and RD
234
When the robot moves to the shooting area which is less
than or equal to the 45 at x-axes, the shooting function will
be operate. The robot will shoot the ball into the goal. The
control statement was used to control the robot for shoot the
ball into the shooting area. When the robot reach area more
than 20 in the y axes or the robot position at the x-axes
between 50 and 60, then robot will stop which is velocity left
and right set as zero.
The R1 will keep detecting the distance between itself and
the ball while it is moving. If the distance between the ball
and R1 is less than 45, R1 will charge the ball into the goal as
shown in Fig.5.
Fig 4: The R1 avoid RD by turning to left side while it is moving to
R’1
IV. CONCLUSIONS
From this research we propose some algorithm for robots
coordination and collaboration in soccer game. We need to
set and adjust the coordinate of the robot position and the
obstacle to make sure the robot can move with obstacle
avoidance, passes and shooting the ball properly. The
synchronization for passing time and robots movements are
made the robot shoots the ball at the shooting area, at the
same time. Our strategy had been tested on robot soccer
simulator. The success of the robot for shooting the ball was
highly depending on the speed of the ball and the robot 1
movement.
Fig 5: The R1 successes to charge the ball into the goal
We aim to improve the stability and velocity of the
robot’s behaviour to kick the ball to the goal in advance.
Hence, we correct the erroneous occurred in the previous
algorithm and understand it as well. From the strategy
algorithm that we have implemented for improvements, we
can clearly distinguish the different type of functions we
have experimented and the effect of it. In our research we
need to set and adjust the ordinate of the robot to make sure
shooting properly. And we also need to synchronize the
timing between two robots, the purpose of the synchronize
are make sure the robot passes the ball at the shooting area,
at the same time, another robot move with obstacle
avoidance and the shoot the ball from the shooting area into
goal.
ACKNOWLEDGMENT
The researchers would like to thanks Anton Heryanto,
Yon Hendri, Muhammad Nuruddin Sudin, Muhamad Syafiq
Shohaimi, and Dwi Yanuar Panji Tresna for their
contribution in this research, University Kebangsaan
Malaysia for providing facilities and financial support under
Operational University Research Grant of Pattern
Recognition Research Group No. UKM-OUP-ICT-26-
186/2010, Arus Perdana No. UKM-AP-ICT-17-2009 and
Fundamental Research Grant Scheme No. FRGS UKM-TT-
03-FRGS0131-2010.
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