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Evolutionary Path Planning Algorithm for Industrial Robots

Fares J. Abu‐Dakka, Francisco Valero, Vicente Mata

Year
2012
Citations
12

Abstract

Abstract This paper proposed a new methodology to solve collision free path planning problem for industrial robot using genetic algorithms. The method poses an optimization problem that aims to minimize the significant points traveling distance of the robot. The behavior of more two operational parameters – the end effector traveling distance and computational time – are analyzed. This algorithm is able to obtain the solution for any industrial robot working in the complex environments, just it needs to choose a suitable significant points for that robot. An application example has been illustrated using robot Puma 560.

Keywords

RobotGenetic algorithmMotion planningPath (computing)Industrial robotComputer scienceAlgorithmMathematical optimizationRobot end effectorArtificial intelligence

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