基于ANFIS的机械手运动学逆解的求取

A Method of Calculating Manipulator Inverse Kinematics Solution Based on ANFIS

提出一种基于自适应神经模糊推理系统(ANFIS)求取机械手运动学逆解的方法。本文以SCARA(Selective Compliance Assembly Robot Arm)型四自由度机械手为研究对象,研究SCARA机械手末端执行器笛卡儿空间坐标与机械手关节空间关节变量之间的对应关系。首先根据笛卡儿运动轨迹选取起点、终点和中间点,并求得与之对应的关节变量值序列。然后利用插值方法求得关节空间的角度变化曲线,最后在关节曲线上随机选取样本点,进而利用得到的数据训练并验证自适应神经模糊推理系统求解逆解的正确性和精确性。与传统基于BP神经网络求取运动学逆解的方法进行仿真对比分析,结果表明ANFIS在运动学逆解的求取精度和运算时间上均优于BP神经网络。

An adaptive neuro-fuzzy inference system（ ANFIS） based inverse kinematics solution of a robotic manipulator is presented. The research object is SCARA type four degrees of freedom manipulator. The corresponding relationship between robot end-effector Cartesian coordinates and manipulator joints space is studied. We select the starting point,intermediate point and end point according to the target trajectory,and use the traditional method to obtain the corresponding joint variable values. Then we get the joints space curve by using cubic splines. Sample points are randomly selected from the curve to train the ANFIS. The results show that ANFIS in calculating precision and computing time of inverse kinematics is superior to the BP neural network.