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Prediction of inverse kinematics of a 5-DOF pioneer robotic arm having 6-DOF end-effector using ANFIS

机译:使用ANFIS预测具有6自由度末端执行器的5自由度先锋机械臂的逆运动学

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In this paper, a method for forward and inverse kinematics analysis of a 5-DOF pioneer robotic arm (PArm) having 6-DOF end-effector is proposed. Obtaining the trajectory and computing the required joint angles for a higher DOF robot manipulator is one of the important concerns in robot kinematics and control. The difficulties in solving the inverse kinematics equations of higher DOF robot manipulator arises due to the presence of uncertain, time varying and nonlinear nature of equations having transcendental functions. In this paper, the ability of adaptive neuro-fuzzy inference system (ANFIS) is used to the generated data for solving inverse kinematics problem. The proposed hybrid neuro-fuzzy system combines the learning capabilities of neural networks with fuzzy inference system for nonlinear function approximation. A single-output Sugeno-type fuzzy inference system (FIS) using grid partitioning has been modelled in this work. The Denavit-Hartenberg (D-H) representation is used to model robot links and solve the transformation matrices of each joint. The forward kinematics and inverse kinematics for a 5-DOF manipulator are analysed systemically.
机译:本文提出了一种具有6-DOF末端执行器的5-DOF先锋机械臂(PArm)的正向和反向运动学分析方法。获取轨迹并计算更高自由度的机器人操纵器所需的关节角度是机器人运动学和控制中的重要问题之一。由于具有先验功能的方程的不确定性,时变性和非线性性质的存在,解决了更高自由度机器人操纵器的逆运动学方程的困难。本文将自适应神经模糊推理系统(ANFIS)的能力用于生成的数据中,以解决逆运动学问题。提出的混合神经模糊系统将神经网络的学习能力与模糊推理系统相结合,用于非线性函数逼近。在这项工作中,已经对使用网格划分的单输出Sugeno型模糊推理系统(FIS)进行了建模。 Denavit-Hartenberg(D-H)表示用于对机器人链接进行建模并求解每个关节的变换矩阵。系统分析了五自由度机械臂的正向运动学和逆向运动学。

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