2 2.1.1 Brief History of Robotic
6 2.1.2 General Structure of Robotic System
7 2.1.3 Type of Robotic System
8 2.1.4 Robotic Arm System
9 2.2 General Robotic Task and Application
10
2.3 Hand Gesture Interaction 11
2.4 Leap Motion Controller and Kinect Sensor 12
2.5 Myo Armband Bracelet 12
2.7 Electromyography EMG 13
2.8 Reviews On Relevant Work 14
2.8.1 Robotic Hand Controlled By Flex Sensor 14
2.8.2 Humanoid Robot Gesture Control 14
2.8.3 Robotic Arm Gesture Control 15
2.8.4 EDGE Robotic Control 15
2.8.5 Robotic Arm Controlled By Flex Sensor 16
2.9 Comparison of Relevant Work 2.10 Summary of Chapter
16 18
3 METHODOLOGY
3.1 Introduction 19
3.2 Hardware and Components Details 19
3.2.1 Myo Gesture Armband 20
3.2.2 Arduino Mega 2560 21
3.2.3 ATX Power Supply 22
3.2.4 Servo Motor 23
3.2.5 Servo Bracket and Servo Holder 24
3.2.6 Base Model 25
3.2.7 Arduino and circuitry 29
3.3 Robotic Arm Assemble Process 3.4 Final Structure of Robotic Arm
30 37
3.5 System Block Diagram 38
3.6 System Integration of Software and Hardware 39
3.6.1 Part A Myo armband and host computer 40
3.6.2 Part B Host Computer and Robotic Arm 41
3.7 Spatial Data Yaw Pitch Roll 43
3.8 Flow Chart of Project 45
3.9 Summary of Chapter 46
4 RESULT AND ANALYSIS
4.1 Introduction 47
4.2 Myo Connect Software Firmware Version 1.3.1448 48
4.3 Spatial Data Analysis Yaw Pitch Roll 54
4.3.1 Yaw Rotation Servo Base 54
4.3.2 Pitch Rotation Servo Wrist 58
4.3.3 Roll Rotation Servo Arm 61
4.4 Gesture event data 64
4.5 Final results 66
5 CONCLUSION AND RECOMMENDATION
5.1 Introduction 76
5.2 Conclusion and recommendation 77
5.3 Importance and Market Potential 78
REFERENCES 79
APPENDIX 81
LIST OF TABLES
NUMBER TITLE PAGE
2.1 Comparison of Relevant Work
12 3.1
Details of Component of Myo Armband 16
3.2 Details on Arduino Mega 2560 Pin Board
17 3.3
Details of Input and Output Voltage and Current 18
3.4 Details of Servo Motor
19
LIST OF FIGURES
NUMBER TITLE PAGE
2.1 Myo Armband Sensor
9
3.1 Components of Myo Gesture Armband
20 3.2
Arduino Mega 2560 21
3.3 ATX Power Supply
22 3.4
Metal Gear Servo Motor 23
3.5 Servo Motor C36R
23 3.6
Servo U-joint Bracket 24
3.7 Servo Motor Holder
24 3.8
One Degree of Freedom of Robotic Arm 25
3.9 Base of Basic Model
25 3.10
Base Design Using AutoCAD 26
3.11 Base of Robotic Arm with Servo Dimension
27 3.12
Base of Robotic Arm 27
3.13 Side Part of Base of Robotic Arm
28 3.14
Lexan Sheet Base With Servo Motor
28 3.15
Circuit Path Proteus Design
29 3.16
Etching Circuit
30 3.17
Robotic Arm Part
30 3.18
Servo Holder Assembled
31 3.19
Holder With Servo Motor
31 3.20
U-joint Bracket
32
3.21
U-joint Bracket Assembled Holder
32 3.22
U-joint Bracket of Base
33 3.23
U-joint Bracket of Wrist Part
33 3.24
Upper Part of Robotic Arm
34 3.25
Gripper Assemble With Servo Holder
34 3.26
Gripper With Servo Assembled
35 3.27
Robotic Arm Gripper
35 3.28
Five Degree of Freedom Robotic Arm
36 3.29
Overview Structure of Robotic Arm
37 3.30
Block Diagram of System Configuration
38 3.31
System Integration Flow Diagram
39 3.32
Flow Chart of Part A
40 3.33
Flow chart of Part B
41 3.34
Axes Rotate of Yaw, Roll, and Pitch
43 3.35
Calculation of Yaw Rotation
44 3.36
Calculation of Pitch Rotation
44 3.37
Calculation of Roll Rotation
44 3.38
Flow Chart of Project Implementation
45
4.1 Myo Connect Software Interface
48 4.2
Myo Calibration Profile 49
4.3 Fist Gesture Calibration
49 4.4
Rest Calibration 50
4.5 Finger Spread Gesture Calibration
50 4.6
Wave in Gesture Calibration 51
4.7 Wave out Gesture Calibration
51 4.8
Test Calibration Profile 52
4.9 Myo Spatial Data
52 4.10
Myo Diagnostic Page 52
4.11 Myo IMU Graph Display
54 4.12
Yaw Angle at Middle Position 55
4.13 Yaw Angle Move in Left Direction
55 4.14
Yaw Angle Move in Right Direction 56
4.15 Recalculated Yaw Angle at Middle Position
56 4.16
Recalculated Yaw Angle Move in Right Direction 57
4.17 Recalculated Yaw Angle Move in Left Direction
57 4.18
Pitch Angle of Wrist Part at Middle Position 58
4.19 Pitch Angle of Wrist Part Turn in Right Direction
59 4.20
Pitch Angle of Wrist Part Turn in Let Direction 59
4.21 Recalculated Pitch Angle at Middle Position
60 4.22
Recalculated Pitch Angle Rotate in Right Direction 60
4.23 Recalculated Pitch Angle Rotate in Left Direction
61 4.24
Roll Angle When Arm at Middle Position 62
4.25 Roll Angle of Arm Moving Upward
62 4.26
Roll Angle of Arm Moving Downward 63
4.27 Recalculated Roll Angle of Arm Moving Upward
63 4.28
Recalculated Roll Angle of Arm Moving Downward 64
4.29
Fist Gesture
65 4.30
Wave Out Gesture
65 4.31
Wave in Gesture
65 4.32
Finger Spread Gesture
65 4.33
Hand at Middle Position 66
4.34 Robotic Arm Base at Middle Position
66 4.35
Hand Move in Right Direction 67
4.36 Robotic Arm Base Move in Right Direction
67 4.37
Hand Move in Left Direction 68
4.38 Robotic Arm Base Move in Left Direction
68 4.39
Hand Move Upward 69
4.40 Robotic Arm Move Upward
69 4.41
Hand Wrist Rotate Right Direction 70
4.42 Robotic Arm Wrist Rotate Right Direction
70 4.43
Hand Wrist Rotate in Left Direction 71
4.44 Robotic Arm Wrist Rotate in Left Direction
71 4.45
Hand Wave in Gesture 72
4.46 Robotic Arm Wrist Move Downward
72 4.47
Hand Wave out Gesture 73
4.48 Robotic Arm Wrist Move Upward
73 4.59
Hand Finger Spread Gesture 74
4.50 Gripper end Open
74 4.51
Hand Fist Gesture 75
4.52 Gripper end Close
75
LIST OF APPENDIXES
APPENDIX TITLE PAGE
A Source Code Javascript Program
82 B
INOTEK Poster 88
C Certificate of Achievement
90
CHAPTER 1
INTRODUCTION 1.1 Background
Nowadays the technologies of the humanoid robot control system has been evolved
tremendously [2] whereby the robotic system can be controlled by using many methods instead of using the remote control unit. One of the important methods is through the hand
gesture performed by humans as a control base to manipulate the robotic system. There are so many industries, the medical field and others start to implement the application
control by using the hand gesture control. It is believed that hand gesture can provide an intuitive based control whereby the robotic system can listen to the feeling of human and
mimicking the hand gesture of humanity [6]. Gesture interface can be built with different sensing techniques such as sensor and mechanical sensor [7]. Recently, there must be
always a need of commands to carry out some specific task thus gesture control is a new innovative technology to improve the our life.
This report uses Myo armband muscle sensor developed by ThalmicLabs to control
the robotic system. The muscle hardware sensor builds in the Myo armband bracelet which consists of Electromyography EMG sensor, nine-axis of IMU containing gyroscope,
accelerometer, and magnetometer. Based on a study of Electromyography EMG, it
normally applies in medical science as a diagnostic procedure to measure the muscle and nerve activity signal during the contraction and relaxation of muscle to detect any of the
muscle disease that related to damage muscle tissues, damage of the nervous system that supplying muscle and others. Due to advanced development of technologies, EMG signal
can be used in a variety of applications such as an embedded control system whereby the signal is recorded from the Myo armband and send it to the microcontroller to let it control
over the robotic system [2].
Besides this paper also extend its work to focus on the structural design of a robotic
system by doing the fabrication after the design process to improve the sustainability as well as the appearance of the hardware. The Myo armband is chosen to implement in this
project because this product is a touch free control device [8], easy to bring along as well as provide more precise signal than the sensor circuit. It detects the information on gesture
performed and there is a platform to analyse data received from the device so that it can be used to communicate with any kind of application control.
This project marked some of the importance attempt to provide a real-time operation
whereby the robotic system can perform the gesture accurately according to the intuitive control of humanity. Besides, the project also provides a simple users hardware without
requiring much of the configuration and the sensor device Myo armband is easy to wear and low cost. The whole robotic system also required less power to process the gesture
because the robotic system only build with servo motor and the Myo armband is rechargeable unless the robotic might be involved in complicated work. Finally, the
concept can be applied in modified ways to any robotic system; which can be developed to demonstrate the approach in a physical rehabilitation application scenario.
1.2 Objectives
