Real-time drogue detection and template tracking strategy for autonomous aerial refueling

Abstract

Autonomous aerial refueling technology is an effective solution to extend flight duration of unmanned aerial vehicles, and also a great challenge due to its high risk. A novel real-time drogue detection and tracking strategy of monocular vision system for autonomous aerial refueling is proposed. It uses a direct image registration-based tracking method to ensure reliable and real-time tracking, and an ROI detection based on edge features to solve the tracking drift problem. A multiply patches fusion structure is adopted in the tracking method to improve the tracking accuracy and slow the divergence speed. Finally, various experiments are conducted to validate the proposed image processing strategy. These results show that the proposed strategy obtains a high accuracy as well as the real-time performance, and achieves a better performance than state-of-the-art methods.