Controlling A Robotic Arm Using Handwritten Digit Recognition Software
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Tarih
2019-03-29
Yazarlar
Dergi Başlığı
Dergi ISSN
Cilt Başlığı
Yayıncı
İstanbul Gelişim Üniversitesi Yayınları / Istanbul Gelisim University Press
Erişim Hakkı
info:eu-repo/semantics/openAccess
Attribution-NonCommercial-NoDerivs 3.0 United States
Attribution-NonCommercial-NoDerivs 3.0 United States
Özet
Abstract- Repetitive tasks in the manufacturing industry is becoming more and more commonplace. The ability to write down a number set and operate the robot using that number set could increase the productivity in the manufacturing industry. For this purpose, our team came up with a robotic application which uses MNIST data set provided by Tensor flow to employ deep learning to identify handwritten digits. The system is equipped with a robotic arm, where an electromagnet is placed on top of the robotic arm. The movement of the robotic arm is triggered via the recognition of handwritten digits using the MNIST data set. The real time image is captured via an external webcam. This robot was designed as a prototype to reduce repetitive tasks conducted by humans. Keywords MNIST Handwritten Digit Recognition, Deep Learning, Embedded System Robotic Arm Control
Açıklama
Anahtar Kelimeler
Research Subject Categories::TECHNOLOGY
Kaynak
International Journal of Engineering Technologies
WoS Q Değeri
Scopus Q Değeri
Cilt
5
Sayı
1
