Implementasi Kalman Filter pada Sistem Pemetaan dengan Sensor Ultrasonik

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The rapid advancement of technology compels social beings to continuously adapt. Robotics, as one of the widely used technologies, offers advantages in solving everyday problems, including room mapping. One of the technologies used to carry out mapping is ultrasonics. Ultrasonic technology utilizes high-frequency sound waves to detect and measure the distance of objects, then converts the reflected wave data into distance or position. A room mapping system uses ultrasonic sensors connected to a central rotating point, generating rotational angle and distance measurements that can be mapped in a graph. The advantages of ultrasonic technology include the ability to map without physical contact and resistance to light and environmental influences, making it ideal compared to optical sensors. However, this technology also has drawbacks in measurement accuracy on non-ideal surfaces. The implementation of the Kalman filter is a solution for reducing fluctuations in ultrasonic measurement results. The effectiveness of the Kalman filter in mapping systems with ultrasonic sensors is measured against the distance results compared to the ideal distance. The results show a reduction in measurement error values with the Kalman filter. Further development is necessary to improve precision and accuracy, making ultrasonic technology more effective in robotics and room mapping applications.