An unsupervised learning based neural network approach for a robotic manipulator

被引：5

作者：

Mahajan A. ^{[1
]}

Singh H.P. ^{[2
]}

Sukavanam N. ^{[3
]}

机构：

[1] Department of Electronics, Sri Venkateswara College, Delhi University, Delhi

[2] Cluster Innovation Centre, Delhi University, Delhi

[3] Department of Mathematics, Indian Institute of Technology, Roorkee

来源：

International Journal of Information Technology | 2017年 / 9卷 / 1期

关键词：

Artificial neural network; Kinematics; Robotic ball catching; Robotic manipulator; Trajectory tracking;

D O I：

10.1007/s41870-017-0002-2

中图分类号：

学科分类号：

摘要：

This paper presents a neural network approach for solving the inverse kinematics of a robotic manipulator. Inverse kinematics equations are more challenging than the forward kinematics equations and therefore are more computationally complex to solve. Here, we are using a neural network approach due to its ability to give more accurate results in complex situations as compared to the other approaches. Moreover, we are using this model for trajectory tracking of a two DOF robotic arm to test its validity in real life situations. © 2017, Bharati Vidyapeeth's Institute of Computer Applications and Management.

引用

页码：1 / 6

页数：5

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