摘要
由于对月球表面障碍物的分布情况不了解,不能建立全局障碍物环境模型,根据传感器所获得的信息建立月球车的局部环境模型,应用模糊模式识别的方法,对在月球上所可能遇到的障碍物的类型进行分类。对不同的类别采用不同模糊控制器用于月球车的自主避障。模糊控制器的输入是离障碍物的最短距离和目标角度信息与环境类别,输出是月球车的转角。采用规则库的自动切换,实现月球车避障过程自适应控制。为了验证该算法的可行性,给出月球车在虚拟环境下的仿真结果。
Because of unknown of obstacle distribution in the lunar surface, whole environment model can＇t be established . But local environment model can be established with ultrasonic sensors. According to fuzzy identification, obstacle environments in the lunar were classified, Using different fuzzy controller for different environments was applied to obstacle avoidance, Inputs of fuzzy controller were shortest distance; angle in relation to target and environment classification and output of fuzzy controller was steering angle, Due to auto-change of rule base, the processing of obstacle avoidance for lunar rover was adaptive controlled, In order to verify the effectiveness of this proposed algorithm, the result of simulation in a computer virtual environment is given.
出处
《计算技术与自动化》
2008年第1期6-8,共3页
Computing Technology and Automation
基金
国家自然科学基金资助项目(50675099)
关键词
模糊模式识别
环境模型
模糊控制器
月球车
fuzzy identification
environment model
fuzzy controller
lunar rover
