Machine vision for automated aerial refueling for unmanned aerial vehicles

explores the application of machine vision in automated aerial refueling for unmanned aerial vehicles (UAVs). Automated aerial refueling has gained significant importance in extending the operational range and endurance of UAVs. Machine vision, a combination of computer vision and machine learning techniques, plays a crucial role in enabling the automation of this process. The paper provides an overview of automated aerial refueling, highlighting its advantages and limitations. It then delves into the role of machine vision and discusses the various techniques involved, including image acquisition and processing, target detection and tracking, pose estimation, and control systems. The challenges and limitations associated with machine vision in aerial refueling are also discussed, including environmental factors, real-time processing, and safety concerns. The paper concludes by highlighting the benefits and future prospects of machine vision in this field, including increased efficiency, improved safety, and integration with autonomous UAV systems. Case studies and experimental results are presented to support the findings.

کلیدواژه ها:

UAV-refueling-machine vision-artificial intelligence