Abstract:
This research paper focuses on the development of a computer vision system for autonomous drone navigation. The objective is to enable drones to navigate and maneuver in complex environments without human intervention. The proposed system utilizes advanced computer vision techniques to perceive and interpret the surrounding environment, allowing the drone to make informed decisions and avoid obstacles. The research explores various algorithms and methodologies for object detection, tracking, and mapping, as well as the integration of these components into a cohesive system. The results demonstrate the effectiveness and potential of the developed computer vision system for autonomous drone navigation.

Table of Contents:

Chapter 1: Introduction
1.1 Background
1.2 Problem Statement
1.3 Objectives
1.4 Scope and Limitations
1.5 Research Methodology

Chapter 2: Literature Review
2.1 Overview of Computer Vision in Autonomous Systems
2.2 Computer Vision Techniques for Object Detection
2.3 Computer Vision Techniques for Object Tracking
2.4 Computer Vision Techniques for Mapping
2.5 Existing Approaches for Autonomous Drone Navigation

Chapter 3: System Design and Implementation
3.1 System Architecture
3.2 Sensor Selection and Integration
3.3 Object Detection Algorithm
3.4 Object Tracking Algorithm
3.5 Mapping Algorithm
3.6 Integration and Communication

Chapter 4: Experimental Evaluation
4.1 Dataset Collection and Preparation
4.2 Performance Metrics
4.3 Experimental Setup
4.4 Results and Analysis
4.5 Discussion of Findings

Chapter 5: Conclusion and Future Work
5.1 Summary of Contributions
5.2 Limitations and Challenges
5.3 Future Directions for Improvement
5.4 Conclusion