Hand Gesture Robotic Arm

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The paper represents the evolution of a hand gesture controlled robotic arm, designed to improve human-robot interaction by providing a natural, automotive interface. Joysticks or remote controllers which are traditional robotic control methods, require crucial user training and can be hard and complex to operate. The proposed system uses a machine vision base webcam that captures user hand movements, the hand gesture commands are processed using machine learning algorithm in Python, which generate commands to robotic arm is controlled via Arduino. The system is trained for real-time responsiveness, to understand a wide variety of hand gestures. Replication accuracy of up to 95% can achieved.