Autonomous drone navigation and obstacle avoidance
Table Of Contents
<p>1. Introduction<br> 1.1 Background and Significance of Secure Software Development<br> 1.2 Objectives and Scope of the Project<br>2. Secure Coding Standards and Best Practices<br> 2.1 Principles of Secure Coding<br> 2.2 Common Vulnerabilities and Mitigation Strategies<br>3. Threat Modeling and Risk Assessment<br> 3.1 Identifying Security Threats and Attack Vectors<br> 3.2 Risk Analysis and Prioritization<br>4. Security Testing and Analysis Tools<br> 4.1 Static and Dynamic Code Analysis Tools<br> 4.2 Penetration Testing and Vulnerability Scanning<br>5. Integration of Security into SDLC<br> 5.1 Secure Development Processes and Methodologies<br> 5.2 Security Training and Awareness for Development Teams<br></p>
Thesis Abstract
<p> This project focuses on the development of autonomous navigation and obstacle avoidance systems for drones using computer vision and machine learning techniques. The project aims to enable drones to navigate complex environments, detect and avoid obstacles in real time, and plan collision-free paths. The research will contribute to the advancement of autonomous aerial vehicles for applications such as surveillance, delivery, and infrastructure inspection. <br></p>Thesis Overview
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