A neuro-genetic-simulated annealing approach to the inverse kinematics solution of robots: a simulation based study. (October 2016)

• Record Type: Journal Article
• Authors: Köker, Raşit; Çakar, Tarık
• Is Part Of: Engineering with computers. Volume 32:Number 4(2016)
• Page Start: 553
• Page End: 565
• Publication Date: 2016-10
• Subjects: Inverse kinematics solution -- Genetic algorithms -- Simulated annealing -- Robotics -- Hybrid intelligent system; Engineering design -- Data processing -- Periodicals; Computer-aided design -- Periodicals; Conception technique -- Informatique -- Périodiques; Conception assistée par ordinateur -- Périodiques; Electronic journals; 620.00285
• DOI: 10.1007/s00366-015-0432-z
• Languages: English
• ISSNs: 0177-0667

Abstract

Abstract In this study, a hybrid intelligent solution system including neural networks, genetic algorithms and simulated annealing has been proposed for the inverse kinematics solution of robotic manipulators. The main purpose of the proposed system is to decrease the end effector error of a neural network based inverse kinematics solution. In the designed hybrid intelligent system, simulated annealing algorithm has been used as a genetic operator to decrease the process time of the genetic algorithm to find the optimum solution. Obtained best solution from the neural network has been included in the initial solution of genetic algorithm with randomly produced solutions. The end effector error has been reduced micrometer levels after the implementation of the hybrid intelligent solution system.