1.4 Problem Statement
2 1.5 Organization of the Report
3
1.6 Summary 4
II LITERATURE REVIEW
5
2.1 Introduction
5 2.2
Genetic Algorithm 6
2.2.1 Genes 6
2.2.2 Fitness 7
2.2.3 Population 8
2.2.4 Data Structures 9
2.2.5 Search Strategies 10
2.2.6 Encoding 10
2.2.6.1 Binary Encoding 11
2.2.7 Breeding 11
2.2.7.1 Selection 12
2.2.7.2 Crossover 14
2.2.7.2.1 Single Point Crossover 15
2.2.7.2.2 Two Point Crossover 16
2.2.7.2.3 Multi-Point Crossover 18
2.2.8 Mutation 18
2.3 Comparison of GA with Other Optimization
Techniques
19
2.4 Advantages of GA in Optimization 19
2.5 Programming Language Environment 20
2.5.1 GA Source Code 20
2.6 Strength and Weaknesses for GA to be Programmed in C Language Compare with Other
Language Environment
20
2.7 Sensors Used in Autonomous Environment 21
2.7.1 Three Axes Accelerometer
– ADXL 330
21 2.7.2 Strength and Weaknesses for GA Use with
Sensors
22
2.8 Microcontroller Used in Autonomous
Environment
22
2.8.1 PIC18F452 23
2.8.2 Comparison of PIC18F452 with
PIC16F877A
25
2.9 Programming Compiler 27
2.10 Software Tool 31
2.11 Summary 32
III METHODOLOGY
34
3.1 Introduction 34
3.2 Description of Methodology 34
3.3 Methodology Flow Chart 35
3.4 Methodology of GA Applied in Autonomous
Helicopter
42
3.5 Summary 44
IV RESULT AND DISCUSSION
45 4.1 Introduction
45
4.2 Fitness Function Used for Helicopter‟s Problems
46
4.3 Result of Output File 47
4.4 Result of Graph Plotting 53
4.5 3
– Axis Accelerometer – ADXL330
56 4.6 Experimental Study
58 4.7 Discussion
60 4.7.1 Compiling Coding
61 4.7.2 Plotting Graph in C Language Environment
62
4.8 Summary 62
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