Kata Pengantar

Abstract

This paper discusses the comparison of digital filters on the accelerometer sensor data to optimize pitch and roll angle measurements from the Inertial Measurement Unit (IMU) system. The accelerometer sensor can be applied to several fields of technology such as robot balancing, advanced surgical tools, navigation systems, attitude-control systems, and others. The accelerometer sensor used in this research is an MPU6050, which includes an accelerometer and a gyroscope sensor. Raw data on the accelerometer sensor is not optimal, so it needs a digital filter to reduce the noise (noise). There are six types of digital filters compared to this research which are low pass filter, average filter, Kalman filter, Finite Impulse Response (FIR), Hanning filter, and exponential filter. To get an optimal variable value (constant) on each filter, It uses a "try and error" method on the accelerometer sensor. The experiment is done by rotating the accelerometer sensor with a reference angle of 0-45 degrees using the Rotary Table. Based on test results, the Kalman filter is the most optimal digital filter for filtering accelerometer data.