面向旋翼无人机目标追踪的解耦视觉伺服方法

Decoupled Visual Servo Method for Target Tracking of Rotor UAV

传统的机器人PID控制方法因结构简单在复杂环境中的鲁棒性与稳定性较差,而传统视觉伺服控制系统的闭环反馈机制影响强耦合系统的控制效果。针对传统机器人PID控制与视觉伺服在旋翼无人机追踪问题中的不足,提出一种解耦的视觉伺服追踪方法。利用费尔曼链码的目标特征提取算法提取目标的特征点,建立特征点误差与速度之间的视觉伺服模型,通过姿态调节去除俯仰角与滚转角的影响,采用动力学扩展方法将运动参数从 4个自由度扩展为6个自由度,设置在线速度空间与角速度空间上独立的伺服增益。在仿真条件与实物条件下进行旋翼无人机追踪实验,结果表明,相比传统的视觉伺服与PID方法,该方法目标丢失概率更小,追踪效果更好。

The traditional robot PID control method has poor robustness and poor stability in complex environment because of its simple structure,while the closed loop feedback mechanism of the traditional Visual Servo (VS) control system affects the control effect of strong coupling system.Aiming at the shortcomings of traditional robot PID control and VS in the tracking problem of rotor UAV,this paper proposes a decoupled VS tracking method.The feature extraction algorithm based on Fehrman chain code is used to extract feature points of target and the VS model of the error of feature point to the velocity is established.The influence of the pitch angle and the rolling angle is removed by the attitude adjustment,the motion parameters are extended from four to six dimensions by the method of dynamic expansion,and the linear velocity servo gain and angular velocity servo gain are set respectively.The tracking experiment of rotor UAV under simulation condition and physical condition is designed.Experimental results show that compared with the traditional VS method and PID method,the proposed method has better target loss probability and better tracking effect.