1. International Journal of Electronics and JOURNALEngineering & Technology (IJECET), ISSN 0976 –
INTERNATIONAL Communication OF ELECTRONICS AND
6464(Print), ISSN 0976 – 6472(Online) Volume 4, Issue 6, November - December (2013), © IAEME
COMMUNICATION ENGINEERING & TECHNOLOGY (IJECET)
ISSN 0976 – 6464(Print)
ISSN 0976 – 6472(Online)
Volume 4, Issue 6, November - December, 2013, pp. 134-139
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IJECET
©IAEME
HOME BUTLER- A VOICE CONTROLLED ROBOT TO ASSIST THE
HANDICAP
GauravJha1,
Addala Sai SubhaCharan2,
Chalasani Rama Krishna Prasad3,
AkashMantry4
1, 2, 3
4
ECE, SRM University, India
ICE, SRM University, India
ABSTRACT
Our system works under voice control. The robot takes in the voice input from the user and
decodes it using LabView. The robot first tells the user whether it can locate the object or not. If it
can, it locates the object and then using another database it gets the image of the object. This is the
reference image and is processed using MATLAB. The histogram of the image is processed. After
finding the specified location of the object and image processing, it uses SLAM (Simultaneous
Localization and Mapping) and goes to the searched location of the object. Using camera vision and
image processing by MATLAB, it tries to find a match with reference image. After getting the
perfect match, it then grips the object by the help of limit switches and photoelectric sensors. Then it
brings the object back to the user by tracing the same path it took to locate it.
Keywords: Voice Control and Decoding, Image Processing, SLAM.
OBJECTIVES
The following are the objectives of our study, which include:
• To get the voice command by the user and decode it effectively.
• To search for the object in our own created database and then locate it and get the
information (histogram) related to it.
• Using Simultaneous Localistaion and Mapping and Light Detection and Ranging sensors, get
to the location of the VR
• Using video camera vision, image processing and comparison by Matlab, find the closest
match of the object.
• Get the distance of the object by using Area Threshold method.
• Move to the object and then grab it using limit switch and photoelectric sensors.
• Bring the object back to the user.
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2. International Journal of Electronics and Communication Engineering & Technology (IJECET), ISSN 0976 –
6464(Print), ISSN 0976 – 6472(Online) Volume 4, Issue 6, November - December (2013), © IAEME
The user gives the voice input to the robot. The robot uses microphone or Easy VR module to
get the voice input. LabView is used to decode the voice to text and also get the location of the
decode
object from our own created database. One method of voice decoding is using the module, which
directly converts voice to text, and the other is using LabView, matching the input with a preloaded
voice signal. Both the input and the preloaded signal are converted to their numerical equivalent and
gnal.
then matched. The robot now has the name of the object. Using the database, it finds the location of
the object and also the particular object’s histogram data in different positions. Using SLAM
technique and LIDAR sensors it finds its path to its destination. The position of the object is obtained
using Localization and then accordingly Mapping builds its map to the destination. LIDAR sensors
consist of a LASER transmitter and a receiver. These sensors help the robot to detect is surroundings
ansmitter
by emitting laser beam through the transmitter and then checking the time it takes for the receiver to
receive the transmitted light, hence, giving it the idea of its surrounding environment and hence,
surrounding
resulting in mapping. Once it reaches its destination, it starts taking in the images of the objects and
processing them. It then finds the closest match by comparing the reference image data and the data
of the image it is viewing. Next step is to find the distance of the object from the robot’s current
ng.
position. It uses Area Threshold method to do it. This method gives us the distance of the object. The
robot then moves to the object and using its grabber grabs it. The grabber consists of limit switch and
consists
photoelectric sensors to assist in grabbing. After grabbing, it brings the object back to the user by
tracing the same path it took to reach its destination This path or map that the robot traced was
destination.
stored in its memory, so that when retracing, it can follow the same path backwards.
at
STRUCTURE
The bot is built on a hard box base with two tyres controlled by maxon motors, the speciality
of these motors is that it has a built in shaft encoder. The shaft encoder gives it a sense of distance
covered and to be covered. These motors are high torque motors so that they can easily mobilize the
bot above. It has a third small tyre at the back to prevent it from toppling. The lower box like base
structure houses the LIDAR structure. It consisits of four pairs of transmitter-receiver LIDAR
c
receiverof
sensors on all the four sides of the box base.
Above the box lies most of the interfacing unit like the camera, microphone and speakers.The
design is simple, it houses a shelf like structure erected on three rods from the base. Out of the three
rods one protrude out of the shelf like structur to a height above it.This rod has a camera on the top
height
along with a microphone.The camera is used for taking in images for processing and comparison
while the microphone takes in the user voice commands.
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3. International Journal of Electronics and Communication Engineering & Technology (IJECET), ISSN 0976 –
6464(Print), ISSN 0976 – 6472(Online) Volume 4, Issue 6, November - December (2013), © IAEME
The shelf like structure houses a pair of speakers for voice output of the robot. It also consists
of flashlights which are swithed on automatically as soon as the light of the environment reduces
below a threshold. Another important part of the self structure is the grabber. It has been designed
anthropologically consisting of a shoulder elbow and wrist. The hand consists of three fingure like
structures.The shoulder is mounted on a servo motor and can move both clockwise and
anticlockwise. The shoulder consisits of another motor combined to cables.These cables being
attached to the elbow. So, when the motor rotates, it coils the cables pulling the arm up, while if the
motor rotates in an anticlockwise direction it releases the cable to put down the arm again.The wrist
is mounted again on a servo motor for clockwise and anticlockwise rotation.The motion of the
fingers is done by using motor cable combination.Three motors are used for the three fingers. When
the motor winds, the cables are pulled and the fingers are moved up, while if the motor is rotated
anticlockwise the cables are released and the fingers go back down.
GRABBER
After the system finds the image at the specefied location, the robotic handmoves towards the
object. When the hand touches the object, the limit switch is triggered which sends the signal to the
microcontroller and then the microcontroller sends the signal to the limit switch. In the robotic arm
we have installed photoelectric sensors which are a type of proximity sensor. The photoelectric
sensors are calibrated for a particular distance according to our requirement. When the robotic arm
moves backward the limit switch opens and now the photoelectric sensors start sensing the object.
The robotic arm moves backward in a linear direction and it stops at a particular distance where it is
calibrated. The linear motion stops and the grabber grabs the object.
DATABASE
After the voice signal has been decoded, the decoded text goes into the database we created
in LabVIEW. The location of the object which has been given as a voice input is found. For eg: If the
user asks for the coffee mug, then the location of the coffee mug which is kitchen is found. We have
created an array of five elements as of now which includes coffee mug, pen, charger, bottle and
brush. And if the user prompts any of these objects then the location of that particular object will be
found. If the user prompts an object which is not in the array, then automatically my LabVIEW
program will give me the voice output as ‘Not found’.
IMAGE PROCESSING
In order to compare the two images we use the technique of histogram.Histogram is basically
a process in which pixels of a particularimage are divided into classes.The main idea is to compare
the small boxes of two images and create an array of values.These valuesare then compared with the
array of values of the reference image.Now there are various possibilities for error to occur in this.
For example suppose 75% of the values in an array are comparable in two images, and then it will
give a result as two images are matched.but remaining 25% may be different.So final result may not
be correct. To avoid thatwe divide the pixels of an image into classes which are further divided into
sub classes and these sub classes are then compared.This gives us a more accurate result as it gives
us more number of values in an array and all the values are compared and the closest result is
given.If the screen resolution of an image is less (say 16*16 pixels) we will get limited values.So
comparison may not be correct.In order to give better result in that case we go for grey scaling of an
image.Also the size of image is reduced to much smaller dimensions.The advantage is that it gives a
better and faster result.
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4. International Journal of Electronics and Communication Engineering & Technology (IJECET), ISSN 0976 –
6464(Print), ISSN 0976 – 6472(Online) Volume 4, Issue 6, November - December (2013), © IAEME
LAB-VIEW Simulated Result
Fig.01
MATLAB Program
Fig.02
THRESHOLD
In some cases when two images have comparable background and the differences are not
visible then values given will be different.To solve this anomaly we go for threshold which is the
minimum value that had to be exceeded in order to be counted.Here you can see the differences
between a 200 pixels wide version of an image and a 100 pixels wide version of the same image.
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5. International Journal of Electronics and Communication Engineering & Technology (IJECET), ISSN 0976 –
6464(Print), ISSN 0976 – 6472(Online) Volume 4, Issue 6, November - December (2013), © IAEME
As we can see that after giving a threshold,the values in an array are getting changed.The
values below '4' are now treated as no difference.This technique is helpful in such cases.Based on the
difference.This
approximation,threshold value of '3' or '4' works in most of the cases.And depending on the task
given you can approximate the value
n
value.
Area Threshold
This method uses a formula that relates the area of pixels and the distance between the object.
This formula is derived before hand for various objects. Depending on the object, we use the
respective formula to determine the distance of it from the robot once it has been detected.
once
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6. International Journal of Electronics and Communication Engineering & Technology (IJECET), ISSN 0976 –
6464(Print), ISSN 0976 – 6472(Online) Volume 4, Issue 6, November - December (2013), © IAEME
Raspberry Pi
Raspberry Pi is basically a operating system. It includes a 700 MHz ARM microprocessor.
We are going to develop software using this OS that contains the database for image location and
image data, and the integration of LabView and Matlab.
CONCLUSION
The purpose of making a Home Butler Robot was to help the disabled person in his day to
day activities. It can fetch things and bring it to the user. There are no such robots made especially
for this application. Our robot is compact and the feasibility is high. However, further advancements
can be made. 3D sensors can be used; better algorithms can be implemented for path finding. We
have just mentioned one technique for the object detection but various techniques can be used. For
SLAM we have used LIDAR but various other sensors can be used along with GPS to make it better.
REFERENCES
1. Image comparison from the abstract submitted by CORNELL UNIVERSITY.
2. www.cmu.edu/herb-robot/‘HERB’ developed in CMU.
3. Kabeer Mohammed and Dr.Bhaskara Reddy, “Optimized Solution for Image Processing
Through Mobile Robots Working as a Team with Designated Team Members and Team
Leader”, International Journal of Computer Engineering & Technology (IJCET), Volume 4,
Issue 3, 2013, pp. 140 - 148, ISSN Print: 0976 – 6367, ISSN Online: 0976 – 6375.
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