Simulation of obstacles’ effect on industrial robots’ working space using genetic algorithm

The study of robot workspace is an interesting problem since its applications are directly related to industry. However, it involves several mathematical complications; Thus, many of the arising questions are left without a definite answer. With the motivation of industrial demand, the need for find...

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Main Authors: M.F. Aly, A.T. Abbas
Format: Article
Language:English
Published: Elsevier 2014-07-01
Series:Journal of King Saud University: Engineering Sciences
Subjects:
Online Access:http://www.sciencedirect.com/science/article/pii/S1018363913000020
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spelling doaj-111e8e52778b40f3844c86753ba27e242020-11-25T01:02:53ZengElsevierJournal of King Saud University: Engineering Sciences1018-36392014-07-0126213214310.1016/j.jksues.2012.12.005Simulation of obstacles’ effect on industrial robots’ working space using genetic algorithmM.F. Aly0A.T. Abbas1Mechanical Engineering Department, The American University in Cairo, New Cairo, EgyptMechanical Engineering Department, Engineering College, King Saud University, P.O. Box 800, Riyadh 11421, Saudi ArabiaThe study of robot workspace is an interesting problem since its applications are directly related to industry. However, it involves several mathematical complications; Thus, many of the arising questions are left without a definite answer. With the motivation of industrial demand, the need for finding better answers than the existing ones lasts. The workspace (WS) determination of a robot with general structural parameters is a complex problem, which cannot be solved in an explicit way. Closed form solutions are only available in some particular cases. Otherwise, computational algorithms and numerical techniques are used. The task becomes even much more complicated by the presence of obstacles in the robot accessible region. Obstacle presence does not only exclude points from the original WS but it affects the whole robot workspace’s shape and size to the extent that it sometimes divides the working space in two or more separate regions that cannot be linked by the same robot. Much research work in the literature is directed toward path planning in the presence of obstacles without having to determine the robot WS. However, a real situation in industry occurs when the knowledge of the WS is of importance in facility layout. This paper presents an approach for the estimation of a generic open-chain robot in the presence of obstacles with any desired number of prismatic and/or revolute joints of any order. Joints’ axes may have any orientation relative to each other. The robot can be placed in free space or in a work cell consisting of a set of Computer Numerically Controlled (CNC) machines and some obstacles.http://www.sciencedirect.com/science/article/pii/S1018363913000020Industrial robotsWorking spaceRobot workspace obstaclesMechanical armsManipulatorsGenetic algorithms
collection DOAJ
language English
format Article
sources DOAJ
author M.F. Aly
A.T. Abbas
spellingShingle M.F. Aly
A.T. Abbas
Simulation of obstacles’ effect on industrial robots’ working space using genetic algorithm
Journal of King Saud University: Engineering Sciences
Industrial robots
Working space
Robot workspace obstacles
Mechanical arms
Manipulators
Genetic algorithms
author_facet M.F. Aly
A.T. Abbas
author_sort M.F. Aly
title Simulation of obstacles’ effect on industrial robots’ working space using genetic algorithm
title_short Simulation of obstacles’ effect on industrial robots’ working space using genetic algorithm
title_full Simulation of obstacles’ effect on industrial robots’ working space using genetic algorithm
title_fullStr Simulation of obstacles’ effect on industrial robots’ working space using genetic algorithm
title_full_unstemmed Simulation of obstacles’ effect on industrial robots’ working space using genetic algorithm
title_sort simulation of obstacles’ effect on industrial robots’ working space using genetic algorithm
publisher Elsevier
series Journal of King Saud University: Engineering Sciences
issn 1018-3639
publishDate 2014-07-01
description The study of robot workspace is an interesting problem since its applications are directly related to industry. However, it involves several mathematical complications; Thus, many of the arising questions are left without a definite answer. With the motivation of industrial demand, the need for finding better answers than the existing ones lasts. The workspace (WS) determination of a robot with general structural parameters is a complex problem, which cannot be solved in an explicit way. Closed form solutions are only available in some particular cases. Otherwise, computational algorithms and numerical techniques are used. The task becomes even much more complicated by the presence of obstacles in the robot accessible region. Obstacle presence does not only exclude points from the original WS but it affects the whole robot workspace’s shape and size to the extent that it sometimes divides the working space in two or more separate regions that cannot be linked by the same robot. Much research work in the literature is directed toward path planning in the presence of obstacles without having to determine the robot WS. However, a real situation in industry occurs when the knowledge of the WS is of importance in facility layout. This paper presents an approach for the estimation of a generic open-chain robot in the presence of obstacles with any desired number of prismatic and/or revolute joints of any order. Joints’ axes may have any orientation relative to each other. The robot can be placed in free space or in a work cell consisting of a set of Computer Numerically Controlled (CNC) machines and some obstacles.
topic Industrial robots
Working space
Robot workspace obstacles
Mechanical arms
Manipulators
Genetic algorithms
url http://www.sciencedirect.com/science/article/pii/S1018363913000020
work_keys_str_mv AT mfaly simulationofobstacleseffectonindustrialrobotsworkingspaceusinggeneticalgorithm
AT atabbas simulationofobstacleseffectonindustrialrobotsworkingspaceusinggeneticalgorithm
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