ANALYZING ACCELEROMETER AND GYRO SENSOR DATA FOR ACCURATE TURNING MOTION

As world manufacturing technologies nowadays are transforming to industry revolution 4.0, autonomous vehicles and equipment enable optimization on production process with minimum of technical error occurrence. Hence, this paper focus on motion of the autonomous vehicle aim to achieve consistent and accurate vehicle turning to maneuver around designated environment. If the locomotion for vehicle turning was not accurate, the overturn error angle will be accumulated over each turn will result in position deviation from the track. The inertia measurement unit (IMU) sensor use for the project comprise of 3 sensor, accelerometer, gyroscope and magnetometer. The axes measured from each sensor will be filter and combined to compute in aircraft principal axes (roll, pitch, yaw) with Madgwick algorithm. A series of test analysis of the IMU sensor performance have been conducted to ensure the data precision over a long period of time. The compute measurement result will be used for controlling motor turning for the autonomous vehicles protype model. The test result on the prototype model indicated the turning accuracy and consistency are able to maintain within an acceptable range of overturn error. The application of IMU sensor with Madgwick algorithm for sensor data enable the use of this sensor with low computational load involved able to achieve real-time functionality for autonomous vehicle locomotion