非结构环境下基于机器视觉的机器人路径跟踪方法

Path Following Control for Mobile Robot Based on Machine Vision In Unstructured Environment

针对温室环境下机器人自主导航问题,提出了基于模糊预测控制的实时路径规划和跟踪方法.通过训练神经网络对图像进行分割,获取导航预瞄点,得到机器人运动的角度偏差和横向偏差.当角度偏差小于25°时,采用预测控制的方法,用拟合圆弧曲线作为机器人跟踪的规划路径,当角度偏差大于25°时,采用模糊控制器对2驱动轮的轮速进行控制.实验表明,该方法能对曲线路径进行平滑的跟踪,以0.3 m/s的速度运动时最大跟踪误差小于5cm.

This paper addresses the problem of autonomous real-time navigation for agricultural robot in greenhouse environment. A novel path planning and tracking method based on fuzzy predictive control was proposed. The navigation preview point was acquired by image segmentation using trained neural network method, then the angle error and the lateral error can be calculated. When the angle error was less than 25 degrees, the robot driving wheels were differential controlled using the planning path which was a fitting circular curve based on predictive control. When the angle error was greater than 25 degrees, the driving wheels＇ speed was controlled by fuzzy controller. The experiments showed that the curve of path tracking was smooth using this method. The most tracking error was less than 5cm at the speed of 0.3 m/s.