Autonomous Detection of Landing pad in Challenging Terrains for Precise Areal Supply

Emerging autonomous Unmanned Aerial Vehicles (UAV) technology is deeply associated with the detection and classification of objects in its Field of View (FOV). Object localization in an image plays an imperative role in UAVs. Detection and localization of objects are crucial in the domain of UAVs, which are essential for military operations. Military bases in hilly or remote places struggle with adequate daily supplies. Communication with the main camp can be challenging due to weak signal strength in certain areas. A fast and accurate delivery to these areas is essential. This study introduces an innovative method to autonomously deliver the supply to the military camps with an onboard camera on a UAV equipped with the You Only Look Once (YOLO) algorithm to detect and accurately calculate the actual location of military camps. The proposed system is trained to identify the landing pads in various challenging environments like blurry areas and stands as a promising advancement in addressing these critical challenges.