Sensor calibration and fusion testing platform

This project aims to create a platform to test the characteristics of IMU devices, get the calibration data, and test and tune different AHRS algorithms. Unmanned vehicles rely heavily on inertial measurement units to determine planar or spatial orientation. Multiple sensory fusion algorithms are developed to obtain the orientation, but even the best algorithms struggle or fail if the sensors are improperly calibrated. As such, in this project, we would like to create an open hardware and software solution based on motorized gimbal architecture to test any inertial measurement unit, obtain the necessary calibration data and test and tune different fusion algorithms (like algebraic quaternion complementary filter, extended/unscented Kalman filter, Mahony and Madgwick filters) After which the sensor and the algorithms can easily be ported into a user application (like a drone, aeroplane, or smartwatch).

Notes:

A detailed technical documentation of the system architecture, implementation, and peripheral testing is provided in the attachments section.

Additionally, the full 3D model of the platform can be accessed here.