Orientation Estimation Through Magneto-Inertial Sensor Fusion: A Heuristic Approach for Suboptimal Parameters Tuning

Magneto-Inertial Measurement Units (MIMUs) are a valid alternative tool to optical stereophotogrammetry in human motion analysis. The orientation of a MIMU may be estimated by using sensor fusion algorithms. Such algorithms require input parameters that are usually set using a trial- and- error (or grid- search) approach to find the optimal values. However, using trial- and- error requires a known reference orientation, a circumstance rarely occurring in real-life applications. In this article, we present a way to suboptimally set input parameters, by exploiting the assumption that two MIMUs rigidly connected are expected to show no orientation difference during motion. This approach was validated by applying it to the popular complementary filter by Madgwick et al. and tested on 18 experimental conditions including three commercial products, three angular rates, and two dimensionality motion conditions. Two main findings were observed: i) the selection of the optimal parameter value strongly depends on the specific experimental conditions considered, ii) in 15 out of 18 conditions the errors obtained using the proposed approach and the trial- and- error were coincident, while in the other cases the maximumdiscrepancy amounted to 2.5 deg and less than 1.5 deg on average.

Automated summary

This article presents a method for suboptimally setting input parameters of sensor fusion algorithms by exploiting the assumption that two rigidly connected MIMUs should show no orientation difference during motion. The approach was successfully validated and tested on 18 different experimental conditions, showing consistent results with the trial-and-error method in most cases.