Vision-Based Navigation Techniques for Unmanned Aerial Vehicles: Review and Challenges

In recent years, unmanned aerial vehicles (UAVs), commonly known as drones, have gained increasing interest in both academia and industries. The evolution of UAV technologies, such as artificial intelligence, component miniaturization, and computer vision, has decreased their cost and increased availability for diverse applications and services. Remarkably, the integration of computer vision with UAVs provides cutting-edge technology for visual navigation, localization, and obstacle avoidance, making them capable of autonomous operations. However, their limited capacity for autonomous navigation makes them unsuitable for global positioning system (GPS)-blind environments. Recently, vision-based approaches that use cheaper and more flexible visual sensors have shown considerable advantages in UAV navigation owing to the rapid development of computer vision. Visual localization and mapping, obstacle avoidance, and path planning are essential components of visual navigation. The goal of this study was to provide a comprehensive review of vision-based UAV navigation techniques. Existing techniques have been categorized and extensively reviewed with regard to their capabilities and characteristics. Then, they are qualitatively compared in terms of various aspects. We have also discussed open issues and research challenges in the design and implementation of vision-based navigation techniques for UAVs.

Automated summary

In recent years, there has been increasing interest in unmanned aerial vehicles (UAVs), also known as drones, in both academia and industries. The advancements in UAV technologies, including artificial intelligence, component miniaturization, and computer vision, have made them more affordable and accessible for various applications and services. The integration of computer vision with UAVs has enabled them to perform autonomous operations in terms of visual navigation, localization, and obstacle avoidance. However, their limited ability to navigate in GPS-blind environments has become a challenge. Visual-based approaches using cheaper and more flexible visual sensors have shown advantages in UAV navigation, particularly due to the rapid development of computer vision. This study aims to provide a comprehensive review of vision-based UAV navigation techniques, categorize and extensively review existing techniques, compare them qualitatively, and discuss open issues and research challenges.