Title :
Connectionist-genetic based algorithm for positioning industrial manipulator
Author :
Tomic, M. ; Miloradovic, B. ; Jankovic, Marija
Author_Institution :
Robot. Lab., Inst. Mihailo Pupin, Belgrade, Serbia
Abstract :
In this paper the solution of inverse kinematics problem and positioning of the industrial manipulator (ROBED03) with five degrees of freedom are presented. The algorithm is based on combination of Artificial Neural Networks (ANN) and Genetic Algorithm (GA).ANN was used for rough positioning providing the inputs for GA which performs precise adjustment. The algorithm was successfully tested in robot´s working space.
Keywords :
genetic algorithms; industrial manipulators; inverse problems; manipulator kinematics; neural nets; position control; ANN; GA; ROBED03; artificial neural networks; connectionist-genetic based algorithm; genetic algorithm; industrial manipulator; inverse kinematics problem; precise adjustment; rough positioning; Artificial neural networks; Genetic algorithms; Joints; Kinematics; Manipulators; Trajectory; Genetic Algorithms; Inverse kinematics; Neural Network and Robot kinematics;
Conference_Titel :
Neural Network Applications in Electrical Engineering (NEUREL), 2012 11th Symposium on
Conference_Location :
Belgrade
Print_ISBN :
978-1-4673-1569-2
DOI :
10.1109/NEUREL.2012.6419964
