Abstract
In recent years, there has been significant growth in applications of Unmanned Aerial Vehicles (UAVs). The demand for an autonomous UAV navigation is growing due to various applications in GPS-denied environments like disaster relief monitoring, search and rescue, mining, bridge inspections, space explorations, and military activities. Visual measurements possess a lot of accurate information which is extracted and exploited for UAV manoeuvring. This paper presents a comprehensive survey of vision-based UAV manoeuvring techniques. The approaches range from deep learning, digital elevation map, and optical flow to mathematical models. The outputs of these techniques cover the various aspects of autonomous navigation like velocity, thrust, yaw angle, heading angle, position, and height. The paper encompasses methods for both indoor and outdoor navigation. The techniques covered mange smooth UAV navigation in different and even unfavourable illumination conditions. Furthermore, this paper serves as a medium to gain insight into the essential aspects of drone navigation methods and their applications.
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