北华大学学报（自然科学版）Issue(1)：123-127,5.DOI:10.11713/j.issn.1009-4822.2015.01.028
模糊自适应卡尔曼滤波技术在球果采集机器人控制系统中的应用
Application of Fuzzy Self-Adapting Kalman Filter in Control System of Pinecone Picking Robot
摘要
Abstract
In order to pick cones automatically,RBF neural network based on fuzzy self-adapting Kalman filter is applied to control the manipulator motion of robot. By programming with MATLAB and solidifying the program to a chip,the data obtained from the three-dimension laser scanner and the sensors on line are processed so as to control the operation of picking cone automatically. The test shows that the automatic control system of RBF neural network is effective and the cones picked by the robot is about 700 ~1 000 kg per day,its efficiency is about 1 . 4~2 . 0 times than that of the robot without RBF control system and about 40~60 times than that of a picker by hand.关键词
模糊自适应卡尔曼滤波/RBF神经网络控制器/球果采集机器人/液压驱动Key words
fuzzy self-adapting Kalman filter/RBF ( radial basis function ) neural network controller/pinecone picking robot/hydraulic drive分类
信息技术与安全科学引用本文复制引用
郭秀丽,亓占丰..模糊自适应卡尔曼滤波技术在球果采集机器人控制系统中的应用[J].北华大学学报（自然科学版）,2015,(1):123-127,5.基金项目
国家自然科学基金项目(51306025) （51306025）
