Aerial-to-Aerial Scene Oriented UAV Recognition and Tracking System
For air-to-air drone identification and tracking task,this paper presents a autonomous recognition and track-ing system based on binocular vision perception and reinforcement learning control.Firstly,target detection is performed using YOLOv8,and a semantic segmentation-based localization algorithm is designed according to the characteristics of binocular vision,achieving rapid and accurate localization of maneuvering targets.Additionally,a filtering algorithm is em-ployed to enhance the reliability of localization information.The tracking process of the target is modeled based on the principles of reinforcement learning,and a tracking controller is trained using the DDPG algorithm.Finally,multiple sets of experiments for identifying and tracking airborne maneuvering targets are conducted on the high-fidelity Airsim simulation platform,validating the effectiveness of the designed drone binocular vision recognition and intelligent tracking system.
UAVbinocular visionDRLaerial-to-aerial tracking system
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