摘要
为了解决单模糊控制器的“规则库爆炸”问题,设计了一种分层的模糊控制器,用于指导移动机器人通过未知环境到达指定的目标点.控制器根据8个超声传感器的信息和目标相对于机器人的方位确定机器人的运动.首先,每个超声传感器的信息被输入到危险度模糊控制器(DFC)中,产生关于周围环境中障碍物危险度的模糊向量.这些模糊向量经过融合与归一化处理后分别输入到上层的速度模糊控制器(VFC)和角速度模糊控制器(RFC)的推理机中.VFC根据目标的距离和障碍物的危险度控制机器人的前进速度.RFC根据目标的方向和障碍物的危险度控制机器人的转向,并采用最大隶属度法的反模糊化策略解决“对称不确定”问题.仿真与实验结果证明了所设计的模糊控制器简单而有效.
This paper presents a hierarchical fuzzy controller for mobile robot navigating from an initial position to a target point through unknown environments. Eight sonar sensors are mounted on the robot to detect obstacles so that the mobile robot can navigate safely. Sonar data and target information are processed by the two-stage fuzzy system to generate the control commands. Firstly, the danger fuzzy controller （DFC） is used for each sonar sensor to judge the danger degree of the detected obstacles. Then, all the outputs of the inference engine are analyzed and normalized by the combination behavior. Finally, the danger information as well as the fuzzified target information is induced by the velocity fuzzy controller （ VFC ） and the rotation fuzzy controller （RFC） respectively to determine the motion of the robot. Maximum defuzzification method is used to solve the “symmetric hesitation” problem. Simulations and experiments validate the performance and effectiveness of the proposed approach.
出处
《机器人》
EI
CSCD
北大核心
2005年第6期481-485,501,共6页
Robot
关键词
移动机器人
导航
避障
模糊控制
分层的
mobile robot
navigation
obstacle avoidance
fuzzy control
hierarchical
