<![CDATA[The balance of unmanned aerial vehicles (UAVs) is crucial to maintain, but there are disturbances from motors and propellers during operation. Additionally, there are unique characteristics of the IMU sensor, namely the sensitive accelerometer and thegyroscope which experiences drift from integration. This research is an analysis of the implementation of the Madgwick filter sensor fusion algorithm (SFA) that combines accelerometer and gyroscope sensor values. The Madgwick filter SFA is implemented on a common IMU, the MPU6050, and an Arduino Nano to test the algorithm on a low-computation microcontroller. Testing showed that the Arduino Nano is capable of computing the Madgwick filter Euler angles at 223 Hz.The parameters of the Madgwick filter SFA are tested by calculating the convergence time of the Madgwick filter SFA output angle with the accelerometer output angle by dropping the sensor on the X-axis. The parameter testing also revealed an output error on the Y-axis due to the Madgwick beta parameter value that amplifies the accelerometer output on the Y-axis. Tests on a quadcopterin hover conditions show that the Madgwick filter SFA output can mitigate disturbances from the harmonic frequencies generated by the quadcopter. Index Terms—Sensor Fusion, Madgwick filter, IMU MPU6050, Quadcopter.]]>
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