中文摘要：

针对使用二维码作为定位模块的视觉自动导引车（AGV）的轨迹跟踪问题,提出了一种基于最优偏差路径的模糊PID纠偏算法。首先建立AGV的运动学方程,将横向偏差和航向偏差作为控制系统的输入变量;其次引入Hamilton最优控制函数,得到基于最优偏差转化策略的AGV最优偏差路径和最优控制方程;最后以AGV与最优偏差路径之间的位姿偏差更新模糊PID控制器的参数,实时调节驱动轮的差速,使AGV按最优偏差路径行驶,实现AGV纠偏的最优控制。实验结果表明,该方法可以平稳、快速地消除横向和航向偏差,本文控制方法在极端偏差状态下的4种隶属度区间的横向偏差纠偏结果分别为2.38、2.54、3.29和4.43 mm,均不超过5 mm,纠偏距离小于1.2 m,跟踪精度为3.2 mm,既提高无轨导引AGV的导航精度,也能较好地满足系统运行的稳定性和伺服驱动能力。

英文摘要：

Aiming at trajectory tracking of the vision-guided AGV with two-dimension code,a fuzzy PID rectification algorithm based on optimal deviation path is proposed. Firstly,the kinematics equation of the AGV is established,using the lateral deviation and course deviation as the input variables of the control system. Secondly,the optimal deviation path and optimal control equation are obtained based on the optimal deviation transformation strategy by introducing the Hamilton optimal control function. Finally,the fuzzy PID controller＇s parameters are updated according to pose error between the AGV and the optimal deviation path,to achieve the differential velocity adjusting real time. As a result,the AGV drives along the optimal deviation path, and achieves optimal control. The experimental results show that the proposed method can eliminate the lateral and course deviation smoothly and quickly. In extreme deviation,the four kinds of membership interval deviation correction results of this method are 2. 38,2. 54,3. 29 and 4. 43 mm. The results are all less than 5 mm,and the rectification distance is less than 1.2 m,and trajectory tracking accuracy is 3.2 mm.Not only the navigation precision improves,but also the stability of the operation and driving capability of the non-track AGV are met.