一种用于跟踪不连续运动目标的视觉伺服方案
A Visual Servoing Scheme for Tracking Discontinuous Moving Targets

视觉伺服中跟踪速度受限的主要原因是处理图像采集、图像处理以及速度估计等带来的延迟。预测算法是处理延迟的一种解决方案，但是预测算法的缺点是对运动目标中的不连续性的预测行为较差。本文提出了一种克服该问题的视觉伺服方案。首先设计了一种新型的前馈–反馈控制方案，将控制系统中的卡尔曼滤波器设置在运动控制器之前，从而获得当前时刻的跟踪目标位置信息，进而减小控制机器人运动的任务函数的取值区间。使用预测监视器监督自适应卡尔曼滤波器的预测质量，如果检测到不连续性，则切换到适当的稳态卡尔曼滤波器，该滤波器比自适应卡尔曼滤波处理不连续性更好。这种新的预测算法能够获得很好的平滑运动和间断运动的预测质量。
The main reason for the limited tracking speed in visual servo is the delay caused by image acqui-sition, image processing and speed estimation. Prediction algorithm is a solution to deal with delay, but the disadvantage of prediction algorithm is that the prediction behavior of discontinuity in moving target is poor. In this paper, a visual servo scheme to overcome this problem is proposed. Firstly, a new feed forward-feedback control scheme is designed, in which the Kalman filter in the control system is set before the motion controller, so as to obtain the tracking target position in-formation at the current time, and then reduce the value range of the task function to control the robot motion. Monitor using Predictive Monitor if discontinuity is detected, the prediction quality of adaptive Kalman filter is switched to the appropriate steady-state Kalman filter, which is better than adaptive Kalman filter in dealing with discontinuity. This new prediction algorithm can obtain good prediction quality of smooth motion and intermittent motion.