Estimasi Sudut Rotasi Benda Kaku Berbasis IMU Menggunakan Kalman Filter - Lasmadi Lasmadi; Freddy Kurniawan; Muhammad Irfan Pamungkas (Aviation Electronics, Information Technology, Telecommunications, Electricals, Controls (AVITEC), 2021)
Rotation angle estimates are often required and applied to the dynamics of spacecraft, UAVs, robots, underwater vehicles, and other systems before control. IMU is an electronic module that is used as an angle estimation tool but has noise that can reduce the accuracy of the estimation. This study aims to develop an estimation model for the angle of rotation of a rigid body based on the IMU-gyroscope sensor on a smartphone using a Kalman filter. The estimation model is developed in a simple dynamic equation of motion in state-space. Kalman filters are designed based on system dynamics models to reduce noise in sensor data and improve measurement estimation results. Simulations are carried out with software to investigate the accuracy of the developed estimation algorithm. Experiments were carried out on several smartphone rotations during the roll, pitch, and yaw. Then, the experimental data obtained is analyzed for accuracy by comparing the built-in algorithms on smartphones. Based on the experimental results, the accuracy rate of estimation angle is 94% before going through the Kalman filter and an accuracy level of above 98% after going through the Kalman filter for every rotation on the x-axis, y-axis, and z-axis.