Raspberry Pis are used to track many things thanks to their compatibility with thousands of modules and sensors. But while most projects rely on monitoring simple data streams like temperature or humidity levels, this project by maker MaxJTihomirov, as they’re known as over at Reddit, plots a more complex measurement. With the help of an IMU module, MaxJTihomirov uses a Raspberry Pi 4 to track physical movement in 3D space digitally.
According to MaxJTihomirov, the project is still in the testing phase, and the source code is not yet ready to share. Still, the project has reached a critical development phase with a working demo shared by MaxJTihomirov showing a digitally traced line within a 3D space. Tracking 3D movement could be applied to various applications, including things like virtual reality, controller input devices, and drones.
The project uses a Raspberry Pi 4 and an Intertial Measurement Unit (IMU) module and Nucleo board. The IMU module provides tools like an accelerometer and gyroscope that the Pi can use to obtain position data. In a comment, MaxJTihomirov explains the Nucleo board is necessary to avoid frequency issues caused by the Raspberry Pi, which can impact the measurement accuracy of the IMU module.
When inquired further into the accuracy of the project, MaxJTihomirov explains the results depend mainly on the quality of the IMU module and any frequency interference. Filters can refine IMU da; MaxJTihomirovov tests the current configuration with Kalman, Mahony, and Madgwick filters.
The source code is not yet publicly available, but plans are in the works to share additional details as the project progresses. Exact steps will vary depending on the IMU module used as libraries can vary between manufacturers. In this project, MaxJTihomirov uses an MP-9250 module—a 9-axis IMU that uses an accelerometer, gyroscope, and magnetometer. Other IMUs would work just as well, but the more sensor data available, the more accurate the 3D tracking will be.
Visit the original thread shared to Reddit for a closer look at this Raspberry Pi project, and be sure to follow MaxJTihomirov for future updates.
