摘要
提出了一种对机器视觉导航的轮式移动机器人进行横向控制的有效算法 ,根据轮式移动机器人运动学模型预测其横向偏差和方位偏差的变化 ,以修正严重滞后的机器视觉采样横向偏差和方位偏差 ,利用修正后的横向偏差和方位偏差设计了系统横向模糊控制器。仿真结果表明 ,该算法有效地克服了因非结构化农田自然环境视觉识别延迟过长所引起的控制系统性能下降的问题 。
In agricultural field, wheeled mobile robot navigated by machine vision is investigated widely at present. This paper presents a lateral predictive fuzzy logic control algorithm for wheeled mobile robot navigated by machine vision. Based on the kinematical model of wheeled mobile robot, the changes of lateral error and heading error can be predicted, with which then the lateral error and the heading error sampled by machine vision can be modified to overcome the long delay produced by machine vision recognizing the characteristics of non structured field environment. With the modified lateral and heading errors as two inputs, a fuzzy logic controller is established to carry out the lateral control of the wheeled mobile robot. Simulation results showed that the lateral predictive fuzzy logic control algorithm possesses good performance and can be adapted to different longitudinal velocity properly.
出处
《农业机械学报》
EI
CAS
CSCD
北大核心
2002年第6期76-79,共4页
Transactions of the Chinese Society for Agricultural Machinery
关键词
视觉导航轮式
移动机器人
横向预测
模糊控制
Wheeled mobile robot, Robot vision, Lateral control, Fuzzy logic control
