IEMEK Journal of Embedded Systems and Applications (대한임베디드공학회논문지)

Institute of Embedded Engineering of Korea (대한임베디드공학회)
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CNN-based Hand Gesture Recognition Method for Teleoperation Control of Industrial Robot

산업용 로봇 원격제어를 위한 CNN기반 손 제스처 인식 방법

  • Received : 2021.01.27
  • Accepted : 2021.04.13
  • Published : 2021.04.30
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Abstract

This paper introduces a teleoperation control system of an industrial robot based on hand gestures using the convolutional neural network (CNN). The proposed system employs the gesture data obtained from an EMG sensor and considers a CNN-based deep learning method. Using the proposed CNN model, we develop a real-time teleoperation control system for the industrial robot. Finally, it is confirmed that the proposed system is reliable in real system since it can be applied to the teleoperation control of a real industrial robot.

Keywords

Acknowledgement

이 연구는 금오공과대학교 학술연구비로 지원되었음 (202001710001).

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