DocumentCode :
236738
Title :
Robot imitation of human arm via Artificial Neural Network
Author :
Durdu, Akif ; Cetin, Halil ; Komur, Hasan
Author_Institution :
Dept. of Electr. & Electron. Eng., Selcuk Univ., Konya, Turkey
fYear :
2014
fDate :
3-5 Dec. 2014
Firstpage :
370
Lastpage :
374
Abstract :
In this study, a robot arm that can imitate human arm is designed and presented. The potentiometers are located to the joints of the human arm in order to detect movements of human gestures, and data were collected by this way. The collected data named as “movement of human arm” are classified by the help of Artificial Neural Network (ANN). The robot performs its movements according to the classified movements of the human. Real robot and real data are used in this study. Obtained results show that the learning application of imitating human action via the robot was successfully implemented. With this application, the platforms of robot arm in an industrial environment can be controlled more easily; on the other hand, robotic automation systems which have the capability of making a standard movements of a human can become more resistant to the errors.
Keywords :
dexterous manipulators; human-robot interaction; intelligent robots; neural nets; ANN; artificial neural network; data collection; human arm imitation; human arm joints; human arm movement; human gesture movement detection; industrial environment; learning application; potentiometers; robot arm; robot movements; robotic automation systems; standard human movements; Artificial neural networks; Joints; Neurons; Service robots; Servomotors; Training; Artificial Neural Networks; Human-Robot Interaction; Learning by Imitation; Robotics;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Mechatronics - Mechatronika (ME), 2014 16th International Conference on
Conference_Location :
Brno
Print_ISBN :
978-80-214-4817-9
Type :
conf
DOI :
10.1109/MECHATRONIKA.2014.7018286
Filename :
7018286
Link To Document :
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