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Attitude Estimation for Indoor Navigation and Augmented Reality with Smartphones

Thibaud Michel 1 Pierre Genevès 1 Hassen Fourati 2 Nabil Layaïda 1 
1 TYREX - Types and Reasoning for the Web
Inria Grenoble - Rhône-Alpes, LIG - Laboratoire d'Informatique de Grenoble
2 NECS - Networked Controlled Systems
Inria Grenoble - Rhône-Alpes, GIPSA-DA - Département Automatique
Abstract : We investigate the precision of attitude estimation algorithms in the particular context of pedestrian navigation with commodity smartphones and their inertial/magnetic sensors. We report on an extensive comparison and experimental analysis of existing algorithms. We focus on typical motions of smartphones when carried by pedestrians. We use a precise ground truth obtained from a motion capture system. We test state-of-the-art and built-in attitude estimation techniques with several smartphones, in the presence of magnetic perturbations typically found in buildings. We discuss the obtained results, analyze advantages and limits of current technologies for attitude estimation in this context. Furthermore, we propose a new technique for limiting the impact of magnetic perturbations with any attitude estimation algorithm used in this context. We show how our technique compares and improves over previous works. A particular attention was paid to the study of attitude estimation in the context of augmented reality motions when using smartphones.
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Submitted on : Friday, March 2, 2018 - 8:48:06 AM
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Thibaud Michel, Pierre Genevès, Hassen Fourati, Nabil Layaïda. Attitude Estimation for Indoor Navigation and Augmented Reality with Smartphones. Pervasive and Mobile Computing, Elsevier, 2018, 46, pp.96-121. ⟨10.1016/j.pmcj.2018.03.004⟩. ⟨hal-01650142v2⟩



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