Development of a low cost inertial measurement unit for UAV applications with Kalman Filter based attitude determination

Abstract

This paper presents the development of an inertial measurement unit (IMU) specially designed for unmanned aerial vehicles (UAV) applications. The design was intended to be a low cost solution of high performance for robotic applications using 3-axis accelerometers and 3-axis gyroscopes MEMS sensors. We present simultaneous sampling to avoid the loss of orthogonality of the inertial measurements due to multiplexed data acquisition commonly used in low cost IMUs, as well as anti-aliasing processing. The IMU was implemented in two boards to separate the sensors from the processing hardware in order to be able to use it with different sets of sensors. The sensor fusion algorithm for attitude determination is based on the Kalman Filter. As testing process, the IMU was installed in a 2-DOF helicopter and the results were compared with those obtained from the encoders for the pitch and roll angles. We also present the results of the IMU installed in a T-REX 450 scale helicopter inside a motion analysis laboratory, using a custom-design safety stand that supports the helicopter allowing only its rotational 3-DOF (roll, pitch and yaw movements). Those demanding experiences tested the IMU performance under true UAV conditions and the results exhibited a maximum RMS error of 4 • .

A Kalman Filter Based Attitude Heading Reference System Using a Low Cost Inertial Measurement Unit

“…To elim-inate this problem, a technique of simultaneous sampling is used, where multiple analog to digital converters measure the different sensors in parallel. It is shown in[39] that the sensors are more capable of correcting errors during high dynamic maneuvers. A common problem with the use of Euler angles is the singularities at ±90 • which are because half angles are used in rotation to represent clockwise and counterclockwise rotation.…”