Visual recognition method of drone formation based on monocular camera

In light of the challenges associated with communication rejection and real-time target detection and three-dimensional perception of visual recognition systems, this paper sets out to investigate the real-time recognition and flight verification of UAV formations utilizing a monocular camera. Visual recognition systems constitute the object of study, while UAV serves as the experimental object. The research firstly focuses on devising visual formation schemes and designing system software and hardware architecture. Subsequently, considering the UAV computing power and real-time performance, a lightweight real-time target detection network is constructed to ensure target recognition speed and accuracy improvement. Relying on real-time target detection combined with ranging function, three-dimensional information of the drone is perceived. Lastly, corresponding data from UAVs is collected to train the algorithm and subsequently verify the efficacy of UAV formation and intrusion. Results indicate that the monocular visual recognition method proposed herein has both real-time detection ability and satisfactory target detection accuracy, which carries immense significance towards the development of UAVs, especially visual formation.