Artificial Neural Networks Applied in the Solution of the Inverse Kinematics Problem of a 3D Manipulator Arm

被引：0

作者：

Dalmedico, Jonatas Favotto ^{[1
]}

Mendonca, Marco ^{[2
]}

de Souza, Lucas Botoni ^{[2
]}

Duarte Barros, Ruan Victor P. ^{[2
]}

Chrun, Ivan Rossato ^{[3
]}

机构：

[1] Fed Univ Technol Parana UTFPR, Mech Engn Dept DAMEC, Cornelio Procopio, Brazil

[2] Fed Univ Technol Parana UTFPR, Eletr Engn Dept DAELE, Cornelio Procopio, Brazil

[3] Fed Univ Technol Parana UTFPR, CPGEI Grad Sch Elect & Comp Engn, Curitiba, Parana, Brazil

来源：

2018 INTERNATIONAL JOINT CONFERENCE ON NEURAL NETWORKS (IJCNN) | 2018年

关键词：

Robotic Arm; Inverse Kinematics; Neural Networks;

D O I：

暂无

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

This paper approaches the classic problem of robotics' Inverse Kinematics. This problem does not have a trivial solution due its solution complexity, in addition to multiple solutions for the same final position of the robotic actuator. The number of solutions increases with the number of degrees of freedom. In this context, the goal of this paper is to present a solution to this problem through the application of an Artificial Neural Network (ANN) in a robotic arm with 4 degrees of freedom in three dimensions. Initial results with a set of seven points using two different ANN configurations were convincing.

引用

页码：787 / 792

页数：6

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