面向速度自适应控制的AGV路径跟踪方法研究

Research on path tracking method of automated guided vehicle for speed adaptive control

针对当前仓储环境下叉车AGV弯道路径跟踪控制精度不足、抗干扰能力弱等问题,结合PID速度控制原理,提出了一种面向速度自适应控制的AGV路径跟踪方法。该方法融合纯跟踪算法和斯坦利算法优点,通过改进算法自适应控制AGV驱动轮转角,可有效弥补传统算法在AGV控制转向时跟踪精度等方面的不足,使AGV较好地运行于期望路径,实现运动路径的最优跟踪。最后通过MATLAB仿真平台,验证了所提算法的优越性。

In the warehouse environment,the forklift automated guided vehicle(AGV)has problems such as insufficient control precision and weak anti-interference ability.Based on the principle of proportional-integral-derivative(PID)speed control,this paper proposes an AGV path tracking method for speed adaptive control.Integrating the advantages of pure tracking algorithm and Stanley algorithm,this method can adaptively control the driving wheel angle of AGV and effectively make up for the shortcomings of traditional algorithms in control turning and tracking accuracy of AGV.The proposed method can enable AGV to run well on the desired path,so it can efficiently achieve the optimal tracking of moving path and effectively improve its working.At last,through the analysis on the Matlab simulation platform,the superiority of the proposed method is verified.