Robotic Arm Movement Control by Gestures Made By Hand Using Signal Processing

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IJRIT International Journal of Research in Information Technology, Volume 3, Issue 6, June 2015, Pg.228-234

Gowtham P G, IJRIT-228 International Journal of Research in Information Technology

(IJRIT)

www.ijrit.com ISSN 2001-5569

Robotic Arm Movement Control by Gestures Made By Hand Using Signal Processing

Gowtham P G¹, Sharathchandra²

1IV Semester, M.Tech, Electronics and Communication Engineering, Sahyadri College of Engineering and Management,Mangaluru, Karnataka, India

[email protected]

2Associate professor, Department of Electronics and Communication Engineering, Sahyadri College of Engineering andManagement, Mangaluru, Karnataka, India

[email protected]

Abstract

Artificial arms are now being used by various industries where there are repeated type of work and where human cannot be present. It can also be involved in dangerous work like diffusing the bomb and taking reading from volcano which is active. So there is requirement for interfacing human brain with the machines here robotic arm. Hand gesture based control is the most convenient way to interact with machine. Hand gesture based recognition algorithm is used widely in electronic circuits. In this project 3-axis accelerometer is used to get the dynamic gesture made by the hand.

I2C protocol based ADC and wireless interface is provided. So that there is complete freedom for the movement of the hand for forming different shapes. Different shapes will be associated with different robotic arm movements. The robotic arm can be operated from a different place and this can work in hazardous place.

Keywords:three axis accelerometer, robotic am, signal processing.

1. Introduction

Automation is a technology or mode of operation in which machine or any part of machine is made to work autonomously without human intervention. The major drawback of this is that it can only replace physical effort not the mental effort. Robotics which is a subset of automation is brought in for this purpose. Here the robotic arm is used. Robotic arm is gaining lot of importance in many industries and also in defense. It is being implemented in many critical and dangerous works like diffusing the bombs, in industries were human cannot work. In this project robotic arm is controlled by hand gestures. Hand gestures are classified into two types dynamic and static. Example for dynamic hand gesture is waving the hand for saying goodbye. Example for static hand gesture is showing stop signal. In this project dynamic hand gestures are used. Three axis accelerometers are used in this project to get the dynamic hand gesture. The gestures created with the help of accelerometer which senses the acceleration and tilts. The predefined gestures are to be created in air in order to control the robotic arm. For example C is made in air with help of accelerometer which closes the gripper or end effector of the robotic arm.

2. System description

This project has two steps:

First is the sensing the motion of the hand in x, y, z direction. The three axis accelerometer is sensing the motion of the hand and the analog data is the converted into digital by using ADC. I2C ADC is used here since this compact and requires very less connections which is efficient and reduces the size, cost and weight. Here only the motion in x and y direction is used. The acceleration values along the x and y

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Gowtham P G, IJRIT-229 direction are digitized by the ADC and sent to the microcontroller which will process the data to generate the hand motion values. In x and y directions. These values will transmitted wirelessly to the robotic arm.

Second part in this project is the controlling the robotic arm by waving the hand in air with the accelerometer. The gestures are predetermined to each action of the robotic arm. These special gestures should be made to control the robotic arm.

Mems technology is growing and has applications in many fields. Here the use of three axis accelerometer is made one of the mems device. Before accelerometer was used in shock sense and tilt sense. In this project tilt sense feature of the accelerometer is not used. In this project acceleration values of the accelerometer are digitized and with signal processing the hand motions from the accelerations are deduced and transmitted wirelessly to the robotic arm.

2.1Advantages

• Keypad based control are considered to be primitive and new technologies are being explored and our project is one such system.

• Being compact and wireless it can be used from anywhere to control anything.

• Shapes to control a device can be redefined with PC interface.

2.2Applications

• This system can be used in industries, home and offices to control various devices.

• Can be used by blinds in smart homes.

• This can be made as integral part of remote you one can control with buttons or gesture whatever user feels more comfortable.

• Mentally challenged and users with cognitive disorders can be trained to use this systems for better learn of hand motion co-relation.

2.3Block diagram

fig1: transmitter side

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Gowtham P G, IJRIT-230 fig2: receiver side

2.4 hardware description

ACCELEROMETERS SENSOR:An accelerometer measures all accelerations other than those accelerations due to gravity, Accelerometer sensors convert either linear or angular acceleration to an output signal. This type of sensors use Newton’s second law of motion, F = ma, by measuring the force from acceleration on an object whose mass is known. An accelerometer is like damped mass on a spring.

The mass of the object is displaced to the point when the accelerometer experiences the acceleration the spring is able to accelerate the mass at the same rate as the casing. The measure of displacement gives the acceleration. Current accelerometers are often little micro electro-mechanical systems (MEMS) and it is also very simple MEMS devices. Using Accelerometers we can measure Acceleration, Inclination, Rotation, Vibration, Collision, tilt and tilt angle, and Gravity etc.

I2C BASED ADC: I2C is special communication protocol and using protocol we will interface to I2C based ADC PCF8591 which used only two wires for control and data acquisition compared to 14 line interfaces to ADC0808 hence it will save space, cost and weight.

MICRO CONTROLLER: For Hand motion we want to use low cost and small in size MCU for making device portable our first choice is 89C2051 or equivalent but if code or data size exceeds we will some higher version. For Main Gesture system we will use P89V51RD2 advance version of 8051 with boot loader feature which help us in fast and hassle free prototyping and code development.

ZIGBEE: CC2500 is wireless transmitter receiver developed by Texas instruments which is used in 2400- 2483.5 MHz ISM/SRD band systems. This is a module which is used in very low power applications i.e.

wireless applications. It is a 2.4 GHz transceiver and also low cost one. The ZigBee transceiver is integrated with a highly configurable baseband modem. It works in voltage range of 1.8 - 3.6V. It has 30m range with onboard antenna. This is always used with microcontroller which support SPI communication.

ROBOTIC ARM WITH DC MOTORS:Four degree of freedom robotic arm is used here. It resembles the human arm there are 5 dc motors in this robotic arm which is used for the movement of the robotic arm.

This similar to human arm which has movements for shoulder, elbow, wrist etc. The end part is the end effector which shows the movement of two fingers

L298 MOTOR DRIVER: L298 46V, 2A Stepper Motor / Dual DC Motor Driver module can drive bipolar stepper motor or Two DC motors together. Each L298 has two H-Bridges. Each H-Bridge can supply 2Amp. Current. Heat sink is provided for better heat dissipation and fly back diodes for protection from back EMF (Electromotive Force). For higher current rating these H-Bridges can be connected in parallel.

Mounting board have four mounting holes. Board has 2pin terminal Block for high power connections.

Board is made of double sided PTH PCB for giving better strength to the connectors.

MICROCONTROLLER:The Texas Instruments MSP430 has a series of ultra-low control microcontrollers.

This comprises of a various devices including distinctive arrangements of peripherals focused for different applications. The architecture is consolidated with five low-control modes and is advanced to accomplish broadened battery life in mobile applications. The MSP430 CPU has a 16-bit RISC architecture that is highly transparent to the application.

3. Implementation

3.1Transmitter side

In this project for controlling the robotic arm this algorithm is developed and this has ten different predefined instructions this is to be processed for working of the robotic arm .Flowchart is developed for this purpose according to which programming is done and it is shown below.

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IJRITInternational Journal of Research in Information Technology, Volume 3, Issue 6, July 2015

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Fig 3: Flow chart for transmitter side 3.2RECEIVER SIDE

The robotic arm consists of 5 dc motors these motors are connected to the microcontroller msp430 through the motor drivers. Different power supplies are provided for the motors and the micro controller. The micro controller performs the actions as the serial data received. The flow chart for this operation is given below.

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Fig 4:flowchart forreceiver side.

4. WORKING

The transmitter part recognizes the hand motion in air and the data from the accelerometer is accumulated and compared with the predefined gestures. Then the instructions are sent to the robotic arm and it performs according to the instructions as shown in the table below.For example let us consider the first example the transmitter moved right down and then left this is like the letter C made in air the accelerometer send the data to the processor through ADC. Then the processor recognizes the gesture and then the send the instruction to the robotic arm part. Robotic

if '1'

if '3'

if '5'

if '7'

if 'U'

if '2'

if '4'

if '6'

if '8'

if 'D' P2.0 OFF

P2.1 0N MOTOR 1

CLOCK

P2.2 OFF P2.3 0N MOTOR 2

CLOCK

P2.0 ON P2.1 OFF MOTOR 1 ANTICLOCK

P1.6 ON P1.7 0FF MOTOR 5 ANTICLOCK any serial data

received init all pin to off(zero)

init serial(9600)

start

configure port pin as output for motor

driver and led

YES NO YES

NO

NO YES YES

YES

NO

NO YES

NO

YES NO

YES

NO YES

NO

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arm works according to the instructions. The table below shows hand motions which are to be made for the functioning of the robotic arm.

Table 1: hand motions and actions by robotic arm

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MOTORS HAND MOTIONS ACTIONS

GRIPPER

RIGHT DOWN LEFT

OPEN LEFT DOWN RIGHT

CLOSE

WRIST

DOWN UP

UP UP DOWN

DOWN

ELBOW

RIGHT LEFT

UP LEFT RIGHT

DOWN

SHOULDER

DOWN RIGHT UP UP

UP RIGHT DOWN DOWN

BASE

DOWN RIGHT RIGHT

DOWN LEFT LEFT

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Fig 5: (a) receiver circuit (b) robotic arm and portable transmitter 5. CONCLUSION

A portable device based on mems is made use for getting the desired commands by hand motions which will control the device. The increasing speed made by the hand movement is measured by the MEMS accelerometer are remotely transmitted to the robotic arm by utilizing ZigBee wireless module. MEMS accelerometer based device is used to control the robotic arm. Robotic arm operates according to the instruction of the transmitter correctly hence there is further possibility of using MEMS based portable devices for human machine interface applications. A simple device like MEMS accelerometer is used here which in turn supports to give accurate and efficient instructions and also this reduces the cost.

References

[1] Ahmad Akl ,Chen Feng and ShahrokhValaee ,”A Novel Accelerometer-Based Gesture Recognition System”

IEEE Transactions On Signal Processing, Vol. 59, No. 12, December 2011

[2] Jeen-Shing Wang and Fang-Chen Chuang, “An Accelerometer-Based Digital Pen with a Trajectory RecognitionAlgorithm for Handwritten Digit and Gesture Recognition”, IEEE Transactions on Industrial Electronics, Vol. 59pp. 2998-3007, 2012.

[3] Bassam Sayed, IssaTraor´e, Isaac Woungang, and Mohammad S. Obaidat , “Biometric Authentication UsingMouse Gesture Dynamics”,IEEEsystems journal, vol. 7, pp. 262-274, 2013.

[4] Sung-Jung Cho, Jong Koo Oh, Won-Chul Bang , Wook Chang , Eunseok Choi , Jing Yang , Joonkee Cho andDong Yoon Kim, “Magicwand: A hand-drawn gesture input device in 3D space with inertial sensors”

,Proceedings of the IEEE ninth International workshop, pp.106-111,2004.