Performance Evaluation of Data Fusion for Orientation Estimation in an Intelligent Inertial Measurement Unit

• Walter Lages UFRGS
• Renato Henriques UFRGS

Abstract

This paper presents a performance evaluation of an intelligent inertial measurement unit (IMU). A 9-axis IMU comprised of a triaxial accelerometer, a triaxial gyroscope and triaxial geomagnetic sensor is considered. The System in Package (SiP) includes a microcontroller running a proprietary sensor fusion software for the estimation of orientation in 3D. The performance of such a system is compared with the performance of an Extended Kalman Filter (EKF) implemented in the host computer and performing a data fusion from the raw not fused data obtained from the same sensors. The sensor is attached to a robot manipulator and orientation estimation of both filters are compared with the ground-truth obtained from the joint sensors of the robot. Results show that the proprietary implementation is not specially good, as the usual EKF was able to match its performance, leaving room for performance improvements by using more advanced filters.

Keywords: Accelerometers, Gyroscopes, Estimation, Kalman filters, Mathematical model, Robot sensing systems, Noise measurement