International Journal of Emerging Technology and Advanced Engineering
Website: www.ijetae.com (ISSN 2250-2459, ISO 9001:2008 Certified Journal, Volume 5, Issue 1, January 2015)
Autonomous Ball Collecting Robot Using Image Processing
Techniques
S. Neeraja1, Roshin Elizabeth Raju2, Asst. Prof. Aravind S3, Roshitha Sara Philip4, Salu Shaji5
1
Student, Sree Buddha College of Engineering for Women, Kerala, India
Asst.Prof, Department of Electronics and Communication, SBCEW, Kerala, India
3
Image processing includes:-
Abstract--There are technologies to control the robot in
many ways. But the use of digital image processing has its own
importance in setting up the control system. The field of image
processing refers to processing digital images by means of a
digital computer. Using this, the robot is designed to collect
the colored objects. In this paper, development of a ball
collecting robot which is equipped with wireless camera for
ball detection is presented. A distance sensor halts the robot
on detecting the object. The object detection is done through
the Matlab code, which provides necessary control signals to
embedded section to pick up the ball. An ultrasonic sensor is
mounted on the robot for obstacle avoidance. The signal from
the Matlab PC is given to the microcontroller and outputs its
decision to the ball picking robot through a Bluetooth
interface. The output decision of the Arduino Microcontroller
is sent to motor driver in order to control the servo motor in
required direction for collecting balls. This method of gaining
control of the robot could be used for performing actions with
more accuracy and ease.
 Importing the image with optical scanner or by digital
photography.
 Analyzing and manipulating the image which
includes data compression and image enhancement.
 Output is the last stage in which the result can be
altered image or report.
In meantime, there has been greater progress in image
processing techniques as it is able to give images in a
computerized form. For digitalization, the provided image
is processed and implemented on a matrix where each pixel
is given a value depending on its color [4]. It is our goal to
implement image processing techniques for a ball
collecting robot using Matlab.
Tennis players develop their skills by repetition.
Nowadays, the balls pick up and its delivery to the balls
dispensing machine is carried out with human intervention,
by using some machines with trolleys but always driven by
humans. In order to improve this task, the need for
dedicated and specialized techniques is becoming a must,
not only to speed up the task but also to reduce the
maintenance costs of the whole system [3]. The traditional
systems do not allow the players to use the field while balls
picking up or maintenance operations are being carried out,
for safety reasons. The extreme violence of one hit in a
human is unbearable. In order to sort out this problem, an
idea came up which consisted of developing an
autonomous mobile platform which carries out the
operation of ball pick up.
Keywords-- Digital Image Processing, Robotic Design,
Bluetooth, GUI Interface.
I. INTRODUCTION
Our world is growing increasingly hunger for time.
Since 18thcenturies, we started to introduce robotics in
every field of applications to reduce human efforts and to
save time. Incorporating image detection process, we can
enhance the features of robots. Using image processing
qualitative information can be extracted by robot for further
functions.
An image can be defined as a two-dimensional function
of f(x, y) where x and y are spatial coordinates and the
amplitude of „f‟ at any pair of coordinates (x, y) is called
intensity of the image at that point [10]. Image processing
is the signal processing for which the input is an image,
such as a photograph or video frame, and the output of this
operation may be a modified image or a set of parameters
put together as a matrix in most cases. Image processing
defines the image in two dimensions and applies certain
image processing techniques such as image enhancement,
image compression, color image processing etc. Digital
image processing is the use of computer algorithms to
perform image processing on digital images [4].
II. THEORETICAL BACKGROUND
The field of digital image processing refers to the
processing of digital images by means of a digital
computer. The image processing is one of the areas of
automation and robotics that, in addition to increasing the
speed of computerized processing systems, further
development has suffered.
One can consider three types of image processing:
165
International Journal of Emerging Technology and Advanced Engineering
Website: www.ijetae.com (ISSN 2250-2459, ISO 9001:2008 Certified Journal, Volume 5, Issue 1, January 2015)
 Processing based on the modification of visual
information characteristics, using optical elements –
lenses and filters. This is a common processing
application in photography, and the level of disclosure
and the level of abstraction.
 Modification of the electrical signal that represents
the image, using analogue electronics.
 Handling characteristics of the digital image. Through
the digital handling of the information element
characteristics – pixel, is acquiring greater
adaptability and flexibility of automated systems [1].
This occurs in an image when there is an edge of two
contrasting colors. For each pixel of the image there is a
corresponding „edge classified‟ 8bit value. A value greater
than 10 was chosen to be the acceptable range of a definite
edge. The size of the value determines the more definite the
contrast. Edge Detection has the potential to assist decision
making in color classification. In the edge-classified image,
an edge may be more than one pixel in width or height.
When comparing images vertically to that of an edge
vertically, it is useful to know if the required image is
within the edge or not, for this reason positive and negative
edge was defined.‟ Positive edge‟ indicates that current
pixel is within the acceptable edge value. „Negative edge‟
is useful for logic scanning down an image.
Color Detection: Color is the perceptual sensation of
light in the visible range incident upon retina. It is the most
striking feature of an image and therefore it is necessary to
understand the concept of color detection in image
processing. It is necessary to identify the color of the ball
so as to avoid the picking of other objects in the track. We
have to transform the picture into grey scale and have to
extract one specific color from the image [6].
Image Enhancement: Image enhancement algorithms
use various methods for editing images to achieve better
image quality [5]. It is used to improve the interpretability
of the information present in the images for human
viewers. The image enhancement algorithms are introduced
to emphasize, sharpen, and smoothen the image features for
display and analysis. Different filters and techniques are
used depending on the application, image content, and
conditions.
Figure 1: Main stages of Digital Image Processing
Figure 1 shows a clear outline of the various stages for
processing digital image – the whole process starts with
image acquisition, which normally corresponds to the
acquisition of light reflections captured by the camera
sensor (CCD) [3].
Shape detection: Shape detection is used for the
recognition of an object and it is a general, domain
independent technique for recognition of patterns in data
analysis. It is basically an attempt to mimic the human
capability to distinguish the image patterns. Various shape
detection procedures are introduced that executes programs
of instruction to implement mathematical algorithm.
"Extend" is a variable used for finding the ratio of the
circle's area to the bounding box's area [5]. This is a useful
parameter in Matlab used to define some features for a
circle. The roundness of the object is detected and draws
the bonding box of the required object.
Edge Detection: Edge detection is necessary to define
other objects in the track [7]. It is necessary to identify the
areas of an image where the change in brightness between
pixels can be detected.
III. CIRCUIT DESIGN
The main components of this prototype are Arduino
Microcontroller, a wireless camera, distance sensor, Zigbee
module. The distance sensor employed will halt the robot
on detecting a particular distance from the object while the
ultrasonic sensor is used for obstacle avoidance. Fig 2
shows the Arduino pin mapping [9]. Arduino is
programmed to convert the analog signals from the sensors
by using the ADC feature of the Arduino microcontroller.
166
International Journal of Emerging Technology and Advanced Engineering
Website: www.ijetae.com (ISSN 2250-2459, ISO 9001:2008 Certified Journal, Volume 5, Issue 1, January 2015)
Every binary information sent from Arduino controls the
servo motors. Based on the particular value received at the
controller the movements of the servos are programmed in
a required way in order to collectyellow colored balls.
WIRELES
CAMERA
HOST
COMPUTER
BALL
COLLECTING
ROBOT
Figure 2 Arduino Atmega328P pin mapping
ZIGBEE
TRANSCIEVER
ARDUINO
MICROCONTROLLER
SENSOR
The output of ADC is fed to the motor driver to enable
the rotation of the motor in the desired direction. A wireless
camera is employed on the ball collecting robot that takes
images at a rate of 50 frames per second. The images are
processed with the help of Matlab code which are
transmitted to the microcontroller through a Zigbee
module. Another Zigbee module acting as the receiver is
attached to Arduino microcontroller. Based on the
particular pattern of binary information received at motor
driver ,the movements of the rover is programmed in the
required way for ball collecting with the help of
programming software Arduino. Arduino is a crossplatform IDE that works in conjunction with an Arduino
controller in order to write, compile and upload code to the
board. [8].
Figure 3 Block diagram representing the concept
The above Figure 3 delineates the complete schematic
diagram of Digital Image Processing for real-time control
of ball collecting robot. Zigbee transmitter sends the host
computer output to Zigbee receiver connected to the
microcontroller. The program loaded on the Arduino is
executed and enables the rotation of DC motor which
performs the desired action.
V. RESULTS AND DISCUSSION
The process was implemented by providing a set of
control signals from the wireless camera. These signals
from the wireless camera are processed by using Matlab
code. The microcontroller is programmed to send
instructions to the ball collecting robot to perform specific
job like ball picking. It is observed that ball collecting robot
is capable of picking yellow balls and place it in the
predefined target. The various stages for the design of the
prototype is shown in the Figure 4 [11][12].
IV. IMPLEMENTATION
The control signal necessary for the real-time
stimulation of ball collecting robot are images from
wireless camera which are processed by a Matlab code
where the object detection is done on the basis of color and
shape. When the object is detected corresponding signals
are fed to the embedded section through a Zigbee wireless
interface. Another Zigbee which is acting as the receiver is
attached with the microcontroller.
The microcontroller receives signals from the host
computer and the sensors.Arduino is programmed to
convert the signals from the sensors to a particular digital
form by using the ADC feature of the Arduino
Microcontroller. The output of the ADC is fed to the motor
driver L293D.
Figure 4 Robot Actions. (a)Halting on ball detection (b)Picking of the
ball
167
International Journal of Emerging Technology and Advanced Engineering
Website: www.ijetae.com (ISSN 2250-2459, ISO 9001:2008 Certified Journal, Volume 5, Issue 1, January 2015)
AUTHORS BIOGRAPHIES
VI. CONCLUSION
The design for a ball collecting robot was presented. The
main function of the robot is to collect small colored tennis
balls and store them into storage areas in a pre-specified
track while avoiding obstacles. The main purpose that the
Robot used is to show the capability of image processing
techniques in real life applications. The challenge arises in
combining the entire image processing techniques
mentioned and robotic designs in one mechatronic system
capable of performing the task in hand; because it is
required to detect edges, colors, and shapes while
commanding the actuators of the robot at the same time. At
last, the era of robots came.
Aravind S, Assistant professor in the
Department
of
Electronics
and
Communication Engineering, Sree Buddha
College of Engineering for Women,
Mahatma Gandhi University, Kerala, India.
He obtained M.Tech degree in VLSI and
Embedded Systems with Distiction from
Govt. College of Engineering Chengannur,
Cochin University in 2012. He received his B.Tech Degree in
Electronics and Communication Engineering with Distiction from
School of Engineering, Cochin University of Science and
Technology, Kerala, India, in 2009. He has published seven
research papers in various international journals. His area of
interest include Network Theory, Signals and Systems, Embedded
Systems, Digital Electronics, DSP and VLSI.
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S.Neeraja, pursuing final year B.Tech
degree in Electronics and Communication
Engineering
from
Mahatma
Gandhi
University, Kerala, India.
Roshin Elizabeth Raju, pursuing final year
B.Tech degree in Electronics and
Communication Engineering from Mahatma
Gandhi University, Kerala, India.
Roshitha Sara Philip, pursuing final year
BTech degree in Electronics and
Communication
Engineering
from
Mahatma Gandhi University, Kerala, India.
Salu Shaji, pursuing final year BTech
degree in Electronics and Communication
Engineering from Mahatma Gandhi
University, Kerala, India.
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