A soft computing approach for inverse kinematics of robot manipulators

被引：64

作者：

Lopez-Franco, Carlos ^{[1
]}

Hernandez-Barragan, Jesus ^{[1
]}

Alanis, Alma Y. ^{[1
]}

Arana-Daniel, Nancy ^{[1
]}

机构：

[1] Univ Guadalajara, Comp Sci Dept, CUCEI, Guadalajara, Jalisco, Mexico

来源：

ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE | 2018年 / 74卷

关键词：

Forward kinematics; Inverse kinematics; Soft computing; Path tracking; OPTIMIZATION;

D O I：

10.1016/j.engappai.2018.06.001

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

The solution of the inverse kinematics problem is an essential capability for robotic manipulators. This capability is used to solve tasks such as path planning, control of manipulators, object grasping, etc. In this paper, we present an approach for solving the inverse kinematics of robot arm manipulators using a soft computing approach. Given a desired end effector pose, the proposed approach is able to solve both the position and orientation for the inverse kinematic problem. In addition, the proposed approach avoids singularities configurations, since, it is based on the forward kinematics equations. We present simulations and experiments, where a comparative study among some selected soft computing algorithms is realized. The simulations and experiments illustrate the effectiveness of the proposed approach.

引用

页码：104 / 120

页数：17

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