ANFIS based kinematic analysis of a 4-DOFs SCARA robot

Jyotindra Narayan, A. Singla
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引用次数: 11

Abstract

Robot kinematics plays a crucial role in recent advancements within industrial sectors and numerous medical applications. Finding forward kinematics, using DH convention is an easy task. As compared to forward kinematics, finding the inverse kinematics solution is far more challenging problem, especially when degrees-of-freedom (DOFs) are more. That is why; there is no general solution to the inverse kinematic problem of a given serial manipulator. This led to the development of alternate technique like fuzzy inference system (FIS) and neural network approach (NNA). This paper uses the combination of above two techniques, called as adaptive neuro fuzzy inference system (ANFIS), along with Gaussian membership function, in order to address the kinematic analysis of a 4-DOFs SCARA robot. The inverse kinematic solutions obtained using ANFIS are further utilized for desired path generation by the SCARA robot. Further, the complete analytical solution is developed in MATLAB environment for the validation purpose. It has been demonstrated with simulation runs that ANFIS results are satisfactory and are found in close approximation with analytical solutions.
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基于ANFIS的四自由度SCARA机器人运动学分析
机器人运动学在工业部门和众多医疗应用的最新进展中起着至关重要的作用。求正运动学,使用DH约定是一个简单的任务。与正运动学相比,寻找逆运动学解是一个更具挑战性的问题,特别是当自由度(dof)更多时。这就是为什么;对于给定的串联机械臂的运动学逆问题,不存在一般解。这导致了模糊推理系统(FIS)和神经网络方法(NNA)等替代技术的发展。本文将上述两种技术相结合,称为自适应神经模糊推理系统(ANFIS),并结合高斯隶属函数,以解决4自由度SCARA机器人的运动学分析问题。利用ANFIS得到的运动学逆解进一步用于SCARA机器人的期望路径生成。并在MATLAB环境下开发了完整的解析解,用于验证。仿真结果表明,ANFIS计算结果令人满意,且与解析解非常接近。
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