模糊CMAC神经网络在机器人装配作业中的应用

Application of Fuzzy CMAC Neural Network in the Robotic Assembly Process

在对机器人销孔装配过程销的装配力与位姿关系实验分析的基础上,设计了机器人主动装配作业的模糊CMAC神经网络系统,采用Takagi型模糊推理方法和有监督的Hebb学习规则,由5自由度装配机器人对直径为12mm的销孔进行了主动装配实验,收到良好的装配效果。

On the basis of the experimental analysis between peg's assembly force and position,which is in the process of robot peg in hole assembly process,a fuzzy CMAC artificial neural network system which can be used in robot active assembly task is developed.Fuzzy CMAC artificial neural network which based on takagi type fuzzy reasoning method is adopted,and it's learning algorithm is analyzed.With the wrist force sensor,the robot active assembly experiments are processed on the assembly robot which is five degree of freedom.The peg-hole assembly task with the diameter of 12 mm and the clearance of 15μm is realized.The experimental result shows that it is a new and effective method in robot active assembly process.