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Next-Generation Computer Vision for Autonomous Drone Navigation: Cutting-Edge Techniques and Real-World Applications
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Author(s): Chikesh Ranjan (National Institute of Technology, Rourkela, India), Jonnalagadda Srinivas (National Institute of Technology, Rourkela, India), P. S. Balaji (National Institute of Technology, Rourkela, India)and Kaushik Kumar (Birla Institute of Technology, India)
Copyright: 2026
Pages: 24
Source title:
Innovative Machine Learning Applications in the Aerospace Industry
Source Author(s)/Editor(s): Venkata Tulasiramu Ponnada (Collins Aerospace, USA)
DOI: 10.4018/979-8-3693-7525-9.ch004
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Abstract
This chapter explores the cutting-edge advancements in computer vision technologies that are revolutionizing autonomous drone navigation. As drones are increasingly deployed in diverse applications such as mapping, surveillance, search and rescue, and delivery services, the need for precise and reliable navigation systems is paramount. The chapter begins with an overview of the fundamental principles of computer vision and its role in enabling autonomous navigation. The integration of machine learning algorithms, such as convolutional neural networks (CNNs) and deep learning frameworks, is discussed, highlighting their impact on enhancing the accuracy and efficiency of drone navigation. Furthermore, the chapter examines practical applications of these techniques, showcasing real-world scenarios where computer vision has significantly improved the performance of autonomous drones. Through this comprehensive examination, the chapter aims to provide valuable insights for researchers, engineers, and practitioners working to advance the field of autonomous drone navigation.
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