Implementation of humanoid robot with using the

IJRET: International Journal of Research in Engineering and Technology eISSN: 2319-1163 | pISSN: 2321-7308
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Volume: 03 Issue: 02 | Feb-2014, Available @ http://www.ijret.org 518
IMPLEMENTATION OF HUMANOID ROBOT WITH USING THE
CONCEPT OF SYNTHETIC BRAIN
Sagar D. Korde1
, Girish R. Talmale2
1
M.E (ESC) – IVth
Semester, 2
Assistant Professor, Department of Computer Science & Engineering GHRCE, Nagpur
Abstract
This paper is elaborate the model of humanoid robot interacts with human being and perform various operation as per the command
given by the human being. A humanoid robot having Synthetic brain can able to do Interaction, communication, Object detection,
information acquisition about any object, response to voice command, chatting logically with human beings. Object detection will be
done by this robot for that purpose there is use image processing concept (HAAR Technique), And to make the system intelligent that
is whenever system interact, communicate, chat with human it gives proper response, question / answers there is integrates artificial
intelligence and DFA / NFA automata and Prolog language concept for answering logically over the complex and relevant strings or
data.
Keywords —Humanoid Robotics, Artificial Intelligence, Image Processing, Audio Filtering.
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1. INTRODUCTION
Synthetic Brain in robotics is an emerging technology.
Synthetic Brain is nothing but the artificial brain and its
working mechanism is just like as human brain. That is this
technology has large scope in engineering science. It may use
to develop the artificial brain of the robot and auto-respond
software is as well.
Synthetic Brain means it is a respond engine respond to
various events occurs in real-time. Like as conversation with
people, performing the multiple-task critical one also,
maintaining large dynamic database for acquisition of
information about any object like fruits, books, etc. Synthetic
Brain in robot is made robot able to discuss with people as per
their mood and topics. I.e. by reading variations of voice
frequencies. Whenever any object will given to identify to
robot, robot eyes means camera’s of robot gets the picture in
frame format analyze it and gives brief information about the
object, like if robot scanning the book as an object, if an
information of that book is already available in the database
then it shows else it acquire data from internet and shows brief
information on any display device i.e. screen or project the
data if projector will interfaced like as Author, type of book,
subject, contains, index, references, etc. Robot will also able
to perform some task like finding the forgotten things like
keys,
There will vast scope to Synthetic Brain to make automated
machines, which are able to take decision on any real-time
event occurred e.g. whenever the robot have conversation with
the human, there is multiple way to respond for that purpose
robot uses DFA/NFA combinations of alphabets to responds.
For designing and implementation of humanoid robot with
synthetic brain four basic technologies are integrated
Robotics, Image Processing, Artificial Intelligence, and Audio
Filtering.
Robotics is used for the modeling purpose of the robots in
which it includes the motion technique. And all the hardware
of the robot with respect to the technology used in robot.
Image Processing is the technique of performing the various
operations on the images for sake of acquiring knowledge and
object detection purpose. Image processing also an effective
technique to respond various Artificial Intelligence technique
in real-time. Artificial Intelligence is nothing but the technique
of creating and implementing various intelligent responses.
Artificial Intelligence is the important objective of project
model which gives ability to robots i.e. acquires knowledge
from the environment. Audio filtering is the technique use for
processing on the voice commands.
2. PROBLEM DEFINITION
A. Robot was working on the static Knowledge concept
therefore it not able to update its knowledge explicitly.
Previously models uses microcontrollers and embedded ‘c’
language for programming and feed the knowledge the
robot which had various limitations to develop the concept
of Artificial Intelligence and training purposes.
B. The previously developed humanoid robots survive in real-
time environment are able to do the task which textually
feed. Basically robot will work only one or hardly two
technologies in combination. If it is able to do conversation
with human then only finite answers and response was
given, it is also not able to acquire knowledge from real-
time environment.

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C. Robot was not navigational mode i.e. not able to navigate
freely in environment. There will absence of image
processing that’s why was not able to process on images.
Due to absence of Image Processing there is lack of
techniques to develop or feeding the knowledge in the
robots.
D. If image processing is present, it is work on very limited
frame segments of image at a particular time slot
Due to absence of audio filtering technique i.e. by FIR filter
whenever robot survive in real-time environment, it can’t be
able to detect right audio command.
3. OBJECTIVES
This paper proposed to develop a humanoid robot which
makes combination of Technologies, which will enhance robot
capabilities in real World by providing synthetic brain.
Technologies involving Humanoid Robotics, Artificial
Intelligence, Image Processing and Audio Filtering. To
develop Humanoid Robot that provides you to intelligent task
performance and interaction with human being using voice
commands as well as text command also. Developing such
Robot in a real-time environment and user can able to give
command to do various complex work like object detection,
searching data on encyclopaedia, pick-up the object which
guided by user and user also can able to chat with Robot.
4. METHODOLOGY
Fig 1: Study & Process Flow
Fig 2: Block Diagram
4.1. Synthetic Brain Concept
Synthetic Brain is nothing but the ability of the robot to give
the proper response to user commands in real-time
environment. For that purpose various techniques are
integrated to give proper responses like detecting the object it
includes the image processing technology(HAAR Technique),
to make robot workable and mobile various motors of
different strength are used, for listening the commands
properly Audio filtering concept is used, For making the
chatting unit in the robot VERBOT technique is used.
4.2. Image Detection Method
Image Processing is used in the project for object detection
purpose by which developer is able to train the robot for
multiple objects.
HAAR Classifier Technique: HAAR classifier is the open
source technique for the Image processing

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Fig 3: Image Detection Block Diagram
a) Creating the description file of positive samples
b) Creating the description file of negative samples
c) Packing the positive samples into a vec file
d) Training the classifier
e) Converting the trained cascade into a xml file
f) Using the xml file to detect the object
4.3. Communication with Robot:
Fig 4: Communication with robot
In the Communication with robot, challenging task is to
provide the voice command. This operation is quite difficult
but due to use of a windows operating system and .net
environment in our robot we can able to take the help of SAPI
5.4. It is a Speech Recognition Application Program Interface
helps us to convert voice command in to text and vice versa.
Fig 5: Mechanism to process on voice command
The SAPI API provides a high-level interface between an
application and speech engines. SAPI implements all the low-
level details needed to control and manage the real-time
operations of various speech engines.
The two basic types of SAPI engines are text-to-speech (TTS)
systems and speech recognizers. TTS systems synthesize text
strings and files into spoken audio using synthetic voices.
Speech recognizers convert human spoken audio into readable
text strings and files.
Fig 6: Block Diagram of Audio filtration
4.4. NFA/DFA Automata:
This algorithm is used for the giving proper dynamic response
to the conversation of the human. That is whenever human
interacts with robot there is multiple combinations of
sentences, words, alphabets are possible. That’s why to give
proper response to human as per his/her mood (detecting by
frequency of voice signal) this automata pattern is used. It is
not only give proper response but also able to adopt new
techniques.

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4.5. Particle Swarm Optimization (PSO):
Particle swarm optimization (PSO) is used for give the
knowledge to the robot regarding with the object and
environmental conditions. And it is very helpful to design the
humanoid model where multiple people are interacts with the
machine.
4.6. RGB, HSI Optimization:
This model uses the not only RGB(Red, Green, Blue) image
attributes but also used HSI model, in which H said hue (hue),
S said saturation (saturation), I indicated that the density
(intensity), corresponding to gray-scale imaging and image
brightness. This is very important technique for detection of
errorless, noiseless and clear image for processing. In the
multitier image attribute system the attributes of image given
to the processing is able to work on the user defined or
customize mode, in which user can customize the attributes of
the image like RGBHSI (Red, Green, Blue, hue, saturation,
intensity),etc. Where as per the user requirement and clarity
requirement the attributes will be manage by user or
programmer.
4.7. Attention Control Phases:
In order to control the human’s attention, we hypothesize
Those robots should perform three consecutive tasks:
(i) Attracting attention (AA)
(ii) Making eye contact (MEC)
(iii) Shifting attention (SA)
Fig. 1 illustrates the conceptual process of attention control
(AC) in terms of sub tasks. To perform a successful AC
process, both robot (R) and human (H) need to show some
explicit behaviors and to respond appropriately to them by
communicative behaviors in each phase. That means, R and H
perform a set of behaviors, R = {φ, ψ, ω} and H = {λ, δ, μ}.
We show that signals for AA, MEC and SA of the robot are
able to control the human attention from one direction to that
indicated by the robot through experiments. In this work, we
apply a set of behaviors of robot such as φ = {head turn, head
shaking, reference terms} in the attracting attention phase, ψ=
{frontal face detection} in the making eye contact phase, and
ω= {head turn} in the shifting attention phase respectively.
We expect that humans also
Perform some responsive behaviors, such as λ = {head/gaze
turn toward the robot, body turn toward the robot} in AA
phase, δ = {keep looking toward the robot while blinking} in
MEC, and μ = {turning head/gaze toward the robot intended
object} in SA phase respectively.
4.8. Motor Driver Circuit & Hubo-Structure:
1. LPT is a port is used for drawn output towards the
L293D Amplification IC.
2. L293D IC is used for the purpose of amplification to
run the relay circuit.
3. There is used Dual relay circuit for operating the
motor in both directions i.e. clockwise and
anticlockwise.
Fig 7: Motor Driver Circuit Diagram and PCB Design
4.9. Use of an Operating System:
The most important feature of our robot is, it carries the
operating system. That’s why we are able to do complex
program and uses various open source techniques and API’s
with respect to our task requirement like as for the purpose of
getting and parsing the voice commands we uses the SAPI 5.4
API of Microsoft corporation, we uses the Open source Verbot
avatars to give proper responses and sensible chatting with
human being in real-time environment, Uses HAAR technique
to image processing.
Operating system not only provides the operating environment
to user but also makes the programmer able to use and
integrate multiple technologies within same robot and co-
ordinately use it as per the task requirement.

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5. HUMANOID ROBOT STRUCTURE AND
SOFTWARE MODULE
Fig 8: Humanoid Robot Structure
Fig 9: Software Modules in Robot
REFERENCES
[1] Dipankar Das, Yoshinori Kobayashi, Yoshinori Kuno
Saitama University, Japan {dipankar,”An Intelligent
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Delconte Politecnico di Torino urin, Italy “Assessment
of rehabilitative exercises by humanoid robot” 2013
7th International onference on Pervasive Computing
Technologies for Healthcare and Workshops
[3] Hao Dang, Youngbum Jun, Paul Oh, and Peter K.
Allen “Planning Complex Physical Tasks for Disaster
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[4] Indrazno Siradjuddin, Laxmidhar Behera, Senior
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IEEE, and Sonya Coleman, Member,” Image-Based
Visual Servoing of a 7-DOF Robot Manipulator Using
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IEEE.
[5] Peng Shengze School of Mathematics and Computer
Science Mianyang Normal University Mianyang,
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[7] George Sineriz_, Michael J. Kuhlman_ and Pamela A.
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[8] Akira Imayoshi, Nagisa Munekata, and Testuo Ono
Hokkaido University, Graduate School of Information
Science and Technology Hokkaido, Japan, “Robots that
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[9] J.Manikandan Crucible of Research and Innovation
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[10] Kazuhiro Nakadai, Gokhan Ince, Keisuke Nakamura,
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[11] “Haar Classifier OpenCV technique for Object
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Interface (SAPI 5.4)”

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