Robot Hand-Controlled by Gyroscope Sensor Using Arduino

The robotic arm’s movements are primarily guided by an accelerometer sensor coupled with an artificial intelligence algorithm. This paper proposes a gesture recognition-based 6DOF robotic arm controller that utilizes a gyro-meter and accelerometer to enhance stability and detect human arm rotational gestures. Equipped with object grasping capabilities, the arm utilizes a sensor fusion approach, combining data from a low-cost MEMS chip housing a 3-axis accelerometer and 3-axis gyroscope, to determine the angular position of objects. This cost-effective solution effectively detects human arm gestures and precisely identifies object orientation. The gyroscope provides gesture orientation data to assess dynamic gesture behavior. An artificial intelligence algorithm evaluates the gesture data, guiding the robotic arm’s training process. The widely used Kalman filter accurately pinpoints the human arm’s position. Wireless communication between the human hand and the robotic arm is facilitated through the IEEE standard Zigbee protocol interface. This enables seamless interaction, with the robotic arm’s movements mirroring human arm gestures in real-time, akin to a shadow mode. The artificial arm’s response to human arm gestures is remarkably swift. This control strategy offers a more intuitive and straightforward approach compared to traditional methods like joystick control, making it well-suited for industrial applications. Developed on the Arduino IDE platform, this robotic arm’s versatility extends to various platforms, including embedded systems and intelligent peripherals. Thus, extensive testing of the robotic arm yielded promising results.