Optimization of Parallel Manipulators Using Evolutionary Algorithms

• Type: Article in International Conference Proceedings Book
• Date: 2010

Authors

Manuel Romano Barbosa (Author) FEUP; Solteiro Pires, EJS (Author) Other; António Mendes Lopes (Author) FEUP

Conference proceedings International

Title: Advances in Intelligent and Soft Computing, Vol 73

Pages: 79-86

Soft Computing Models in Industrial and Environmental Applications, 5th International Workshop (SOCO 2010)

Guimarães, Portugal, 16 a 18 de Junho 2010

Indexing

ISI Web of Knowledge - 7 Citations

Other information

Authenticus ID: P-003-CXE

DOI: 10.1142/9789812839442_0003

Abstract (EN): Parallel manipulators have attracted the attention of researchers from different areas such as: high-precision robotics, machine-tools, simulators and haptic devices. The choice of a particular structural configuration and its dimensioning is a central issue to the performance of these manipulators. A solution to the dimensioning problem, normally involves the definition of performance criteria as part of an optimization process. In this paper the kinematic design of a 6-dof parallel robotic manipulator for maximum dexterity is analyzed. The condition number of the inverse kinematic jacobian is defined as the measure of dexterity and solutions that minimize this criterion are found through a genetic algorithm formulation. Subsequently a neuro-genetic formulation is developed and tested. It is shown that the neuro-genetic algorithm can find close to optimal solutions for maximum dexterity, significantly reducing the computational load.

Language: English

Type (Professor's evaluation): Scientific

No. of pages: 8