산업용 로봇 원격제어를 위한 CNN기반 손 제스처 인식 방법
CNN-based Hand Gesture Recognition Method for Teleoperation Control of Industrial Robot
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초록
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.
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.
참고문헌 (18)
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