Design of Speech Recognition Based Robotic Arm

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International Journal of Advanced Engineering Science and Technological Research (IJAESTR) ISSN: 2321-1202, www.aestjournal.org @2015 All rights reserved

29

Design of Speech Recognition Based Robotic Arm

Farooq Ahmad Tantray

¹

,Mrs. Shimmi S L

²

, Dr. Lini Mathew

³

, Department of Electrical Engineering,

National Institute of Technical Teachers Training And Research Chandigarh Punjab university

[email protected]

Abstract--Speech is one of the natural forms of communication. Recent development has made it possible to use this in the security system and controlling the devices. In speech recognition, the task is to use a speech sample to select the identity of the person that produced the speech from among a population of speakers. This paper is to describe a robotic arm cum Gripper for handicapped person using voice technology. The aim of the project is to give the facility to the handicapped or disabled people who have lost their arm or hand in war or accident and are not able to carry objects like a cup of tea or spoon to feed them. Speech recognition technology makes the control of arm easier as voice is used to control it, using voice recognition module, microphone and microcontroller. Speech recognition module is trained with certain command which the user wants the circuit to recognise with the help of a microphone which is interfaced with voice module to enable voice based recognition. The movement of wrist at joints is achieved using motors at joint locations whose speed is controlled by voice commands of user. The methodology adopted is based on grouping a microcontroller with a speech recognition system

Index Terms— speech Recognition System, Degree of freedom, (DOF)

.

I Introduction

End effecter is a generic term that includes all the devices that can be installed at a robotic wrist.

Grippers are the most common type of end effecter.

The control of the end effecter is done by the robotic controller which in this paper is based on speech recognition. If persons with upper limb disabilities were to have access to robotic arms that provide degrees of flexibility similar to healthy arms and hands, they could perform numerous daily life activities by themselves, such as drinking, eating, reading books and letters, operating cell phones, etc. all of which would normally require the assistance of another person. In such situations, the robotic arms would provide more freedom and independence to disabled users and thus improve their quality of life. The work to design a controller involves the development of software programme and design of a gripper based on speech recognition

technology. The voice recognition is done by HM2007 voice recognition IC. The microphone is directly connected at the analog input of voice recognition IC HM2007 keeping the mode selection key in the record mode. The microcontroller ATMEGA8 along with motor driver L293D is used to drive and control the DC motors at various joint locations.

II Block Diagram

Fig.1 Block Diagram Depicting voice Recognition Based Robotic Arm

III Working

Speech recognition module is trained with certain command with the help of a microphone and a keypad. This module generates a code for each voice command. The generated codes are applied to controller module which generates the operating signal for a particular joint (motor) .The microcontroller is programmed, process the commands and generate an activation signal at a particular output port Voice recognition module is interfaced with microcontroller The output generated signals of microcontroller are supplied to the a particular joint (motor)through a driverIC.

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International Journal of Advanced Engineering Science and Technological Research (IJAESTR) ISSN: 2321-1202, www.aestjournal.org @2015 All rights reserved

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The driver IC operates the motor using separate dc source. It also changes the direction of the rotation of motor depending upon the enable signal.

IV

Hardware Involved

A. HM2007

The voice recognition IC HM2007 is capable of operating in speaker independent speech recognition mode. In speech recognition mode, first, the voice is recorded to the external SRAM attached to the IC with the help of a directly connected microphone at the analog input terminal of HM2007 keeping the mode selection key in the record mode. In this way 40 0.9second long words or 20 1.92-second long words or phrases can be recorded into the memory. After training the voice recognition IC like above the mode selection key is switched to voice input mode. Here at a particular instant the speech through the microphone is compared with the recorded sound and according to that digital output is generated. The output of voice recognition IC is then fed to the digital input ports of the ATMEGA328 microcontroller. The microcontroller on receiving the Signal directs the motors through the control circuit. The control of speed and direction are done in this way. The change of direction is achieved by changing the direction of current flow through the motor and speed control is achieved by varying the current through the motor.

Fig.2 Voice Module

B. ARDUINO (ATMEGA328)

The microcontroller on the board is programmed using the arduino programming language and arduino development environment. Arduino programming provides a number of libraries to make programming easier. The most simplest of these are functions to control and read the I/O pins.

In this project voice recognition module output is connected to analog pins of the arduino. The arduino programming is written such that, based on the switch state of the speech recognition sensor output values are processed and the direction and

speed of the motors are controlled through the motor driver circuit.

Fig.3 Arduino

C. L293D IC

The L293D motor driver is available for providing user with ease and user friendly interfacing for embedded application. L293D motor driver is mounted on a good quality, single sided non-PTH PCB. The pins of L293D motor driver IC are connected to connectors for easy access to the driver IC’s pin functions. The L293D is a dual full bridge driver that can drive up to 1Amp per bridge with supply voltage up to 24V. It can drive two DC motors, relays, solenoids, etc. The device is TTL compatible. Two H bridges of L293D can be connected in parallel to increase its current capacity to 2 Amp.

Fig. 2.7 shows the driver Ic in the form of a module with terminal blocks and connectors to make it easy to connect with the circuit.

Fig.4 L293D

D. Microphone:

Microphones are a type of transducer - a device which converts energy from one form to another.

Microphones convert acoustical energy (sound waves) into electrical energy (the audio

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International Journal of Advanced Engineering Science and Technological Research (IJAESTR) ISSN: 2321-1202, www.aestjournal.org @2015 All rights reserved

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signal).Different types of microphone have different ways of converting energy but they all share one thing in common: The diaphragm. This is a thin piece of material

( such as paper, plastic or

aluminium) which vibrates when it is struck by sound waves. In a typical hand-held mic like the one below, the diaphragm is located in the head of the microphone.

Fig. 5 Microphone

V. Software Implementation:

The microcontroller ATMEGA 322 is programmed using C language. Programming is done on the computer system using arduino open source. 2 bit data from voice recognition module is fed to arduino analog input terminals A0 to A2. The command analog-read is used to read the status of analog pins. Based on the status of the analog pins appropriate command is generated by arduino to actuate a particular joint of the arm.

As per the code used to programme arduino if the status of analog pins is 00000010 the command generated for arm would be shoulder forward various commands generated for different inputs from voice recognition module can be observed on the serial monitor of arduino.

Figure 6 Arduino Program Various steps of programming are shown as

flowchart in Figure 7

Fig. 7

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International Journal of Advanced Engineering Science and Technological Research (IJAESTR) ISSN: 2321-1202, www.aestjournal.org @2015 All rights reserved

32 VII Gripper Unit

A gripper is a device which enables the holding of an object to be manipulated. The easier way to describe a gripper is to think of the human hand.

Just like a human hand a gripper enables holding, tightening, handling and releasing of an object. It is attached to the arm. The gripper grips and releases the objects by activating appropriate motors using controlling command from arduino. The input to the arduino is the digital out of voice recognition module. The digital output depends upon the voice command of the disabled person.

In robotics, end effectors are a device at the end of a robotic arm, designed to interact with the environment. Gripper is an end effecter or tool to grasp any physical thing that may be human hand or any instrument. A DC motor is used using gears and a threaded shaft arrangement. The gripper can perform the basic function of picking, holding and grasping of irregularly shaped objects.

Our project aim is to build a gripper for a robotic arm. To achieve this goal a simple linkage mechanism is incorporated along with DC geared motors. The human hand design forms the basis of this project of developing a robotic gripper and is the source of great inspiration to achieve the sufficient level of dexterity in the domain of grasping and manipulation if coupled with wrist and arm.

Degree of freedom is a very important term to understand. Each degree of is a joint on the arm ,a place where it can bend or rotate or translate. You can typically identify the no of dof by the no of actuators on the robotic arm. It is an important term when fabricating a robotic arm. Each degree requires a motor. Figure 8 shows the gripper used in the robotic arm.

Fig. 8 A Gripper

The motors used are 12v DC BO motors. The commands used to open and close the Gripper are Gripper open and Gripper close. The digital output generated by voice module is:

Gripper open: 00001010 Gripper close: 00001001

The command generated by arduino for the Gripper can be seen on serial monitor as shown in below figure.

Fig.9 Com 6

Fig.10 Serial Monitor Showing Gripper Operation

VIII Wrist

The kinematic structure of the robotic arm allows to position its end pointy at any (x,y,z) location in the 3D space. In order to provide for the proper orientation of the hand/end –effecter the robotic arm should have a wrist. Typically a robotic wrist

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International Journal of Advanced Engineering Science and Technological Research (IJAESTR) ISSN: 2321-1202, www.aestjournal.org @2015 All rights reserved

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provides the same 3D rotation as a human hand:

roll, pitch and yaw.

The command used by the user to move the wrist I,e to give it three degrees of freedom are -Wrist forward, wrist backward and the corsponding digital output generated is:

Wrist farward: 00000111 Wrist backward: 00001000

The command generated by arduino for the wrist can be seen on serial monitor as shown below.

Fig.11 A Wrist

Fig.12 Serial Monitor Showing Wrist forward Operation

IX . Elbow

The command used by the user to move the elbow up and down are –Elbow up

^and

Elbow down and the corresponding digital output generated is:

Elbow up: 0000 0101 Elbow down: 0000 0110

The command generated by arduino for the elbow can be seen on serial monitor as shown below.

Fig. 13 An Elbow

Fig. 14 Serial Monitor Showing Shoulder- Up Operation

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International Journal of Advanced Engineering Science and Technological Research (IJAESTR) ISSN: 2321-1202, www.aestjournal.org @2015 All rights reserved

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Fig.15 Serial Monitor Showing Elbow Down

Operation

X. SHOULDER

The command used to move shoulder up, down, forward and backward open and close the Gripper are shoulder up shoulder down, shoulder forward and shoulder Backward. The digital output generated by voice module is:

Shoulder up: 0000 0001 Shoulder down: 0000 0010 Shoulder forward: 0000 0011 Shoulder Backward: 0000 0100

Fig 16. Shoulder Joint The command generated by arduino for the shoulder can be seen on serial monitor as shown below.

Fig.17 Serial Monitor Showing Shoulder- Up Operation

Fig.18 Serial Monitor Showing Shoulder-Down Operation

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Fig.19 Serial Monitor Showing Shoulder-

Backward Operation

Fig.20 Serial Monitor Showing Shoulder- Farward Operation

The prototype model developed is shown in the figure 7.8 below.

Figure 21 Prototype Model Of The Robotic Arm.

XI.Conclusion

The present work includes the design and development of Voice Recognition Based Robotic Arm using ATMEGA 322 microcontroller.

The Voice Recognition Based Robotic Arm is an assistive device which has high demand biomedical sector. It is voice based and does not involve any assistance of other hand. The disabled person independently performs many tasks like lifting glass of water, move things around etc.

The Voice Recognition Based Robotic Arm has three main parts: Voice Recognition Module,

Atmega 322 microcontroller and power supply section. First of all training of the voice module is done using the voice commands of the user. Voice module is then connected to arduino and the output of the arduino goes to robotic arm. To operate the arm the operator commands are compared to the previously recorded voice. When the command matches a digital signal is generated as output. This output is fed to arduino. The arduino further directs the appropriate motors through the generated control signal. Arduino is programmed using C language. Arduino open source code.

The major difficulties in developing this Voice Recognition Based Robotic Arm

were to reduce

power consumption, cost effectiveness, motor selection.

The following steps were followed in design and development of Voice Recognition Based Robotic Arm.

 Proper choice of the microcontroller (Atmega322).

 Proper choice of the voice Recognition System.

 Proper choice of the motors.

 Designing proper circuitry.

 Final implementation of the developed Voice Recognition Based Robotic Arm using PCB.

 Testing of the developed Voice Recognition Based Robotic Arm with a proper model.

The investigator here concludes that a Voice Recognition Based Robotic Arm is developed.

XII. Future work and possible upgradation

The designed prototype model of Voice Recognition Based Robotic Arm needs to be upgraded before its commercialisation.

For the future enhancement of the Voice Recognition Based Robotic Arm-

i. It can also be made to operate using EMG signal.

ii. Some other controlled sensors like thought, facial expression can be added for the patients who cannot speak.

iii. More degrees of freedom can be added to make the arm more flexible.

iv. It can be made stronger to lift higher weights using motors of higher rating.

XIII. References

[1]. Jamshed Iqbal, Raza ul Islam, and Hamza Khan “ Modeling and Analysis of a 6 DOF Robotic Arm Manipulator’’

Canadian Journal on Electrical and Electronics Engineering , pp 300-306 ,Vol. 3, No. 6, July 2012

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[2]. Vishnu Prabhu S and Dr. Soman K.P

‘’Voice Interfaced Arduino Robotic Arm for Object Detection and Classification’’

International Journal of Scientific and Engineering Research, Volume 4, Issue 7, pp 445-449,2010

[3]. Mohammed Faeik Ruzaij S.Poonguzhali

“Design and Implementation of Low Cost Intelligent Wheelchair”, ICRTIT pp 468- 471, 2012

[4]. Ryszard Tadeusiewicz . “Speech in Human system Interaction”. In this paper some general remarks about the how speech human system interaction are presented and some problems connected with this activity are described, pp 2-13 May 13-15,2010

[5].

Mr. Sangmeshwar , S Kendre and Prof.

S.D Apte “Voice Controlled Robot using Open Source Hardware Platform Beagleboard” international journal of recent trends in Engineering and Technology, pp 101-105 vol 4,No.4, Nov.

2010.