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Abstract

We are studying the accuracy of attitude estimation algorithms in the context of pedestrian navigation using standard smartphones and their inertial and magnetic sensors.

Scientific findings

We examine the typical motions of smartphones when carried by pedestrians. We use ground truth data obtained from a motion capture system. We present an in-depth comparison and experimental analysis of existing algorithms for attitude estimation. Our experiments highlight, for the first time, the relative impacts of calibrations, noise, biases, motion, magnetic disturbances, and sampling rates on attitude estimation in smartphones.

Scientific Review

We are continuing our research on this topic through Thibaud Michel’s ongoing doctoral thesis at UGA on mobile augmented reality applications for smart cities.

Coordinators

Pierre Genevès, LIG, pierre.genevescnrs.fr (pierre[dot]geneves[at]cnrs[dot]fr)
Hassen Fourati, GIPSA-lab, hassen.fouratigipsa-lab.grenoble-inp.fr (hassen[dot]fourati[at]gipsa-lab[dot]grenoble-inp[dot]fr)

Most Significant Publication

T. Michel, P. Genevès, H. Fourati, N. Layaïda. "Attitude Estimation with Smartphones," IEEE International Conference on Pervasive Computing and Communications (PerCom), March 2017.