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Dergiler / International Journal of Engineering Technologies / 2026 / Cilt: 5 Sayı: 1

Controlling A Robotic Arm Using Handwritten Digit Recognition Software

Ali Çetinkaya(Technology Transfer Office, Istanbul Gelisim University)0000-0003-4535-3953
Onur Öztürk(School of Management, Faculty of Engineering, University College London (UCL))
Ali Okatan(Department of Computer Engineering, Faculty of Engineering, Istanbul Gelisim University)0000-0002-8893-9711
Sayfa
15–23
Yayın Tarihi
2019-03-29
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Yapay Zeka Hızlı Bakış & Çıkarımlar

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⚡ TL;DR(1 Cümlede Hızlı Çıkarım)

This robot was designed as a prototype to reduce repetitive tasks conducted by humans.

📌 3 Maddede Bu Makale

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Amaç & Hipotez:Repetitive tasks in the manufacturing industry is becoming more and more commonplace.
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Temel Bulgular & Veri:The ability to write down a number set and operate the robot using that number set could increase the productivity in the manufacturing industry.
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Sonuç & Katkı:This robot was designed as a prototype to reduce repetitive tasks conducted by humans.
🔬Tür:Araştırma Makalesi
📍Kapsam:Genişletilmiş Akademik Örneklem
⚙️Değişkenler:MNIST Handwritten Digit Recognition · Deep Learning · Embedded System Robotic Arm Control

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 Tensorflow 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.

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Bu Makaleye Atıf Yap

Çetinkaya, A., Öztürk, O., Okatan, A. (2019). Controlling A Robotic Arm Using Handwritten Digit Recognition Software. International Journal of Engineering Technologies, Cilt: 5 Sayı: 1, 15–23. https://doi.org/10.19072/ijet.462378

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Kaynakça (17)

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