Implementation of Kalman filter on the accelerometer balance sensor and ultrasonic obstruction sensor in two-legged robot applications

The use of the Kalman Filter in a two-legged robot balance system has been carried out to minimize the effect of noise on the robot control system. The research was conducted by analyzing and comparing the balance system of the robot with two different methods, namely the robot without the Kalman Filter and the robot with the Kalman Filter. The analysis includes several parameters, such as the angle of movement of the robot, the distance the robot travels, the frequency of falling and the time it takes the robot to reach the target. The average test results obtained without the Kalman Filter process are for the robot movement angle of 25.42°, the success of the robot’s mileage is 37.86% of the predetermined target distance and the frequency of falling the robot is 4.2 times and the robot travel time is 59.42° seconds to reach the target distance. While the average test with the Kalman filter process is the robot movement angle of 22.94°, the success of the robot’s mileage is 100% of the predetermined target distance. These results prove that the Kalman Filter method is able to minimize noise so that the robot’s performance in maintaining its balance and maneuvering increases.