Together, the MPU6050 and HMC5883L form a complete 9-degree-of-freedom (9-DOF) orientation sensing system capable of providing stable pitch, roll, and heading information.

A Kalman Filter is a mathematical algorithm that helps engineers determine the most accurate estimate of a system's state by combining sensor measurements with predictive models. Originally developed for aerospace applications, Kalman Filters are widely used in rockets, satellites, aircraft, and autonomous systems to reduce sensor noise and improve navigation accuracy.

This project shows how an MKR/MKT1010 and MPU6050 sensor can turn real motion into a live 3D visualization. Using Arduino IDE and Processing, raw accelerometer and gyroscope data is converted into roll, pitch, and yaw, then displayed as a moving rocket or aircraft model in real time.