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Introduction

The advancement of drone technology has opened up a wide range of applications in various fields such as surveillance, search and rescue, package delivery, agriculture, and mapping. One of the key challenges in drone technology is autonomous navigation, where the drone is able to navigate and make decisions without human intervention. Autonomous drone navigation requires the integration of various technologies such as sensors, machine learning, computer vision, and control systems to enable the drone to navigate safely and efficiently in complex environments. This thesis focuses on the development of autonomous drone navigation systems to improve the navigation capabilities of drones and enhance their performance in real-world applications.

1.1 Introduction
1.2 Background of study
1.3 Problem Statement
1.4 Objective of Study
1.5 Limitation of Study
1.6 Scope of Study
1.7 Significance of Study
1.8 Structure of the Thesis
1.9 Definition of Terms

Chapter Two: Literature Review

2.1 Overview of Autonomous Drone Navigation
2.2 Technologies for Autonomous Navigation
2.3 Challenges in Autonomous Navigation
2.4 Existing Autonomous Navigation Systems
2.5 Applications of Autonomous Drone Navigation
2.6 Current Research Trends in Autonomous Navigation
2.7 Sensor Fusion Techniques for Autonomous Navigation
2.8 Control Strategies for Autonomous Navigation
2.9 Machine Learning Algorithms for Autonomous Navigation
2.10 Performance Metrics for Autonomous Navigation Systems

Chapter Three: System Design and Methodology

3.1 System Architecture
3.2 Sensor Selection and Integration
3.3 Data Collection and Processing
3.4 Path Planning Algorithms
3.5 Obstacle Avoidance Strategies
3.6 Decision-making Algorithms
3.7 Simulation and Testing Environment
3.8 Performance Evaluation Metrics

Chapter Four: System Implementation

4.1 Hardware Setup
4.2 Software Implementation
4.3 Integration of Sensors and Systems
4.4 Calibration and Testing
4.5 Performance Optimization
4.6 Real-world Testing and Validation
4.7 System Robustness and Reliability
4.8 System Maintenance and Upgrades

Chapter Five: Conclusion and Summary

5.1 Summary of Findings
5.2 Contributions to the Field
5.3 Future Research Directions
5.4 Conclusion

Thesis Overview:

Autonomous drone navigation is a critical aspect of drone technology, allowing drones to operate independently in various environments. This thesis focuses on developing autonomous navigation systems for drones to improve their navigation capabilities and enhance their performance in real-world applications. The thesis begins with an introduction to autonomous drone navigation, discussing the background of the study, problem statement, objectives, limitations, scope, significance, structure, and definition of terms related to the topic.

The literature review in Chapter Two provides an overview of autonomous drone navigation, technologies for autonomous navigation, challenges, existing systems, applications, research trends, sensor fusion techniques, control strategies, machine learning algorithms, and performance metrics. Chapter Three details the system design and methodology, including system architecture, sensor selection, data collection, path planning, obstacle avoidance, decision-making algorithms, simulation, and testing. Chapter Four focuses on system implementation, covering hardware setup, software implementation, sensor integration, calibration, testing, performance optimization, real-world testing, system robustness, reliability, and maintenance.

In the Conclusion and Summary chapter, the findings are summarized, contributions to the field are discussed, future research directions are suggested, and the thesis is concluded. The thesis aims to advance the field of autonomous drone navigation and contribute to the development of more efficient and reliable drone navigation systems for a wide range of applications.

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