Image-Based Visual Servoing for Quadrotor Formation Encirclement and Tracking of Unknown Targets

A target state estimation method based on multiple quadrotors is proposed for unknown maneuvering targets, and a distributed formation control method Image-Based Visual Servoing (IBVS) is also proposed to achieve encirclement tracking of unknown maneuvering targets. In the tracking control, collision avoidance constraints for nodes within the formation are also introduced, and based on the shared position information within the formation, the positions of other nodes within the Field of View (FOV) of each node are predicted for detecting unknown targets. Firstly, an Interacting Multiple Model (IMM) was designed based on multiple motion modes to estimate the position and velocity of the target. A virtual camera coordinate system containing translational and yaw rotations was established between the formation and the target based on the estimated values. Then, a distributed control method based on IBVS was further designed by combining image deviation. At the same time, a safe distance between nodes within the formation was introduced, and collision avoidance constraints of the Control Barrier Function (CBF) were designed. Finally, the position of the formation nodes within the FOV was predicted. The simulation results demonstrate that, utilizing the proposed estimation method, the estimation accuracy for target velocity improves by 26.5% in terms of Root Mean Square Error (RMSE) compared to existing methods. Furthermore, the proposed control method enables quadrotor formations to successfully achieve encirclement tracking of unknown maneuvering targets, significantly reducing tracking errors in comparison to conventional approaches.