An artificial intelligence approach to forward kinematics of Stewart Platforms

Author

Morell, Antonio ; Acosta, Leopoldo ; Toledo, Jonay

Author_Institution

Dept. de Ing. de Sist. y Autom. y Arquitectura y Tecnol. de Comput. (ISAATC), Univ. de La Laguna, La Laguna, Spain

fYear

2012

fDate

3-6 July 2012

Firstpage

433

Lastpage

438

Abstract

The Stewart Platform, one of the most successful and popular parallel robots, has attracted the attention of many researchers in recent decades. The solution of the forward kinematics problem in real-time is one of the key aspects that continues to garner interest. In this paper we propose a new approach for solving this particular case using Support Vector Machines, a popular Machine Learning method for classification and regression. The algorithm involves a data generation and preprocessing off-line phase, and a fast on-line evaluation. The experiments show that this method is very accurate and suitable for use in real-time.

Keywords

learning (artificial intelligence); mechanical engineering computing; pattern classification; regression analysis; robot kinematics; support vector machines; Stewart platforms; artificial intelligence approach; classification; data generation; forward kinematics; machine learning method; offline data preprocessing phase; online evaluation; parallel robots; regression; support vector machines; Actuators; Kinematics; Mathematical model; Parallel robots; Support vector machines; Training; Vectors; Forward Kinematics; Parallel Robots; Stewart Platform; Support Vector Machines; Support Vector Regression; real-time;

fLanguage

English

Publisher

ieee

Conference_Titel

Control & Automation (MED), 2012 20th Mediterranean Conference on

Conference_Location

Barcelona

Print_ISBN

978-1-4673-2530-1

Electronic_ISBN

978-1-4673-2529-5

Type

conf

DOI

10.1109/MED.2012.6265676

Filename

6265676