https://github.com/acetinkaya/controlling-a-robotic-arm-using-hand-recognition-software

Controlling A Robotic Arm Using Hand Recognition Software
https://github.com/acetinkaya/controlling-a-robotic-arm-using-hand-recognition-software

embedded-system-robotic-arm-control gesture-recognition opencv opencv-python

Last synced: about 1 month ago
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Controlling A Robotic Arm Using Hand Recognition Software

• Host: GitHub
• URL: https://github.com/acetinkaya/controlling-a-robotic-arm-using-hand-recognition-software
• Owner: acetinkaya
• License: mit
• Created: 2019-11-07T11:53:43.000Z (over 5 years ago)
• Default Branch: master
• Last Pushed: 2024-11-22T22:14:07.000Z (7 months ago)
• Last Synced: 2025-03-31T22:41:34.379Z (3 months ago)
• Topics: embedded-system-robotic-arm-control, gesture-recognition, opencv, opencv-python
• Homepage: https://dergipark.org.tr/en/pub/ijet/issue/45163/462339
• Size: 626 KB
• Stars: 7
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

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README

        
# Controlling-A-Robotic-Arm-Using-Hand-Recognition-Software

Controlling A Robotic Arm Using Hand Recognition Software

## Authors

- [**Ali Çetinkaya**](https://scholar.google.com.tr/citations?user=XSEW-NcAAAAJ)  

  Department of Electronics Technology, Istanbul Gelisim Vocational School, Istanbul Gelisim University, Istanbul, Turkey

- **Onur Öztürk**  

  School of Management, Faculty of Engineering, University College London (UCL), United Kingdom

- **Ali Okatan**  

  Department of Computer Engineering, Faculty of Engineering and Architecture, Istanbul Gelisim University, Istanbul, Turkey

*For Correspondence: [email protected]*

## Article Information

- **Received**: September 21, 2018  

- **Accepted**: April 27, 2029

- **Full Article Access Link**: [Controlling A Robotic Arm Using Hand Recognition Software](https://dergipark.org.tr/en/pub/ijet/issue/45163/462339)

![alternatif metin](https://github.com/acetinkaya/Controlling-A-Robotic-Arm-Using-Hand-Recognition-Software/blob/master/arm1.png)

## Abstract:

With the increasing need of repetitive tasks in the manufacturing industry, robotic automation is becoming a necessity. In the steel industry, workers become less efficient over time, causing interruptions during assembly. Robotic automation is capable of operating at highest efficiency therefore increasing productivity in the steel industry. The robot will be able to pick up and drop metallic object with the help of the electromagnet present on the robotic arm. The handling of the objects will be triggered by the hand gestures from the user. The image to be processed will be captured by an external camera. This robot is built as a prototype for the steel industry. 

## Keywords: Gesture Recognition, OpenCV, Embedded System Robotic Arm Control, Embedded C.

## How to Cite

- **IEEE**: A. Çetinkaya, O. Öztürk, and A. Okatan, “Controlling A Robotic Arm Using Hand Recognition Software”, IJET, vol. 5, no. 2, pp. 59–63, 2019.	

- **APA**: Çetinkaya, A., Öztürk, O., & Okatan, A. (2019). Controlling A Robotic Arm Using Hand Recognition Software. International Journal of Engineering Technologies IJET, 5(2), 59-63.	

- **MLA**: Çetinkaya, Ali et al. “Controlling A Robotic Arm Using Hand Recognition Software”. International Journal of Engineering Technologies IJET, vol. 5, no. 2, 2019, pp. 59-63.	

## License

Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0)

![alternatif metin](https://github.com/acetinkaya/Controlling-A-Robotic-Arm-Using-Hand-Recognition-Software/blob/master/arm2.png)