Gyroscope and Accelerometer Calibration with Raspberry Pi

This is the second entry into the series entitled "Calibration of an Inertial Measurement Unit (IMU) with Raspberry Pi" where the gyroscope and accelerometer are calibrated using our Calibration Block. Python is used as the coding language on the Raspberry Pi to find the calibration coefficients for the two sensors. Validation methods are also used to integrate the IMU variables to test the calibration of each sensor. The gyroscope shows a fairly accurate response when calibrated and integrated, and found to be within a degree of the actual rotation test. The accelerometer was slightly less accurate, likely due to the double integration required to approximate displacement and the unbalanced table upon which the IMU was calibrated. Filtering methods are also introduced to smooth the accelerometer data for integration. The final sensor, the magnetometer (AK8963), will be calibration in the next iteration of this series.

Calibration of an Inertial Measurement Unit (IMU) with Raspberry Pi - Part I

Inertial measurement units (IMUs) can consist of a single sensor or collection of sensors that capture data meant to measure inertial movements in a given reference frame. Acceleration, speed of rotation, and magnetic field strength are examples of sensors contained in an IMU. IMUs can be found in applications ranging smart devices, medical rehabilitation, general robotics, manufacturing control, aviation and navigation, sports learning, and augmented and virtual reality systems. Inertial measurement units have become increasingly popular as their form factors shrink and computational power increases. The ability to use IMUs for indoor/outdoor tracking, motion detection, force estimation, orientation detection, among others has caused the use and availability of inertial sensors to become nearly widespread in smart phones, smart watches, drones, and other common electronic devices. The internet is full of projects involving accelerometers, gyroscopes, and magnetometers, but few cover the full calibration of all three sensors. In this project, the manual calibration of a nine degree-of-freedom (9-DoF) IMU is explored. A common MPU9250 IMU is attached to a cube to manually find the calibration coefficients of the three sensors contained within the IMU: accelerometer, gyroscope, and magnetometer. The IMU is wired to a Raspberry Pi - which will allow for high-speed data acquisition rates of all nine components of the IMU.

Force Sensitive Resistors (FSRs) with Arduino

A force sensitive resistor (FSR) is comprised of a conductive polymer material pressed between two electrode layers, giving it the ability to electrically respond to changes in stress and strain. FSRs are often used in ergonomic or rehabilitation applications where pressure is applied from human interaction and the response is recorded or translated. Force sensitive resistors are incredibly useful for human interactivity because of their slim profile, inexpensive construction, and multiplicative geometries. The sensor used in this tutorial is the RP-S40-ST, which is a 40mm x 40mm thin film FSR. An Arduino board will be used to read the analog signals outputted by the FSR in a voltage divider configuration, where the force applied to the FSR can be approximated using the sensor’s calibration curve.