Inertial Odometry on Handheld Smartphones

Tutkimustuotos: Artikkeli kirjassa/konferenssijulkaisussavertaisarvioitu

Tutkijat

Organisaatiot

  • Tampere University of Technology

Kuvaus

Building a complete inertial navigation system using the limited quality data provided by current smartphones has been regarded challenging, if not impossible. This paper shows that by careful crafting and accounting for the weak information in the sensor samples, smartphones are capable of pure inertial navigation. We present a probabilistic approach for orientation and use-case free inertial odometry, which is based on double-integrating rotated accelerations. The strength of the model is in learning additive and multiplicative IMU biases online. We are able to track the phone position, velocity, and pose in realtime and in a computationally lightweight fashion by solving the inference with an extended Kalman filter. The information fusion is completed with zero-velocity updates (if the phone remains stationary), altitude correction from barometric pressure readings (if available), and pseudo-updates constraining the momentary speed. We demonstrate our approach using an iPad and iPhone in several indoor dead-reckoning applications and in a measurement tool setup.

Yksityiskohdat

AlkuperäiskieliEnglanti
Otsikko2018 21st International Conference on Information Fusion, FUSION 2018
TilaJulkaistu - 2018
OKM-julkaisutyyppiA4 Artikkeli konferenssijulkaisuussa
TapahtumaInternational Conference on Information Fusion - Cambridge, Iso-Britannia
Kesto: 10 heinäkuuta 201813 heinäkuuta 2018
Konferenssinumero: 21

Conference

ConferenceInternational Conference on Information Fusion
LyhennettäFUSION
MaaIso-Britannia
KaupunkiCambridge
Ajanjakso10/07/201813/07/2018

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