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Neuro-Fuzzy Inference System based controller in 6 DoF in PUMA 560

机译:PUMA 560中基于6 DoF的Neuro-Fuzzy推理系统的控制器

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摘要

One of the problems in robotics field is, to find the orientation and framing of arm's end to desired location there for the new method must be find the solution of forward and inverse Kinematics (IK) problem. Traditional methods such as iterative, geometric and algebraic are used to solve (IK) inadequate if the joint structure of the robot is more complex. As the complexity of manipulator increases, solution of IK is difficult and computationally expensive. In this paper the use of the ability of Adaptive Neuro-Fuzzy Inference System (ANFIS) to learn from training data is implemented. Then the creation of ANFIS with limited mathematical representation of the system is performed. In the proposed method, forward kinematics relations of robot arm are used to obtain the data for training and testing of ANFIS. Simulation using MATLAB and microcontroller is used to show the effectiveness of the approach. Also the practical results which are carried out on PUMA 560 with 6DoF robot arm are used to show the effectiveness of the approach and proved that this method has good performance.
机译:机器人技术领域的问题之一是,要找到手臂末端的方向和框架到所需位置,对于新方法,必须找到正向和反向运动学(IK)问题的解决方案。如果机器人的关节结构较复杂,则使用迭代,几何和代数等传统方法来解决(IK)不足的问题。随着操纵器复杂性的增加,IK的求解变得困难且计算量大。在本文中,使用了自适应神经模糊推理系统(ANFIS)从训练数据中学习的能力。然后,使用系统的有限数学表示来创建ANFIS。在该方法中,利用机器人手臂的正向运动学关系来获取用于ANFIS训练和测试的数据。使用MATLAB和微控制器进行的仿真表明了该方法的有效性。并在带有6DoF机械臂的PUMA 560上进行的实际结果也证明了该方法的有效性,并证明了该方法的良好性能。

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