A square root inverse filter for efficient vision-aided inertial navigation on mobile devices

Kejian Wu, Ahmed M. Ahmed, Georgios A. Georgiou, Stergios Roumeliotis

Research output: Chapter in Book/Report/Conference proceedingConference contribution

52 Scopus citations

Abstract

In this paper, we present a square-root inverse sliding window filter (SR-ISWF) for vision-aided inertial navigation systems (VINS). While regular inverse filters suffer from numerical issues, employing their square-root equivalent enables the usage of single-precision number representations, thus achieving considerable speed ups as compared to double-precision alternatives on resource-constrained mobile platforms. Besides a detailed description of the SR-ISWF for VINS, which focuses on the numerical procedures that enable exploiting the problem's structure for gaining in efficiency, this paper presents a thorough validation of the algorithm's processing requirements and achieved accuracy. In particular, experiments are conducted using a commercial-grade cell phone, where the proposed algorithm is shown to achieve the same level of estimation accuracy, when compared to state-of-the-art VINS algorithms, with significantly higher speed.

Original languageEnglish (US)
Title of host publicationRobotics
Subtitle of host publicationScience and Systems XI, RSS 2015
EditorsJonas Buchli, David Hsu, Lydia E. Kavraki
PublisherMIT Press Journals
ISBN (Electronic)9780992374716
DOIs
StatePublished - 2015
Event2015 Robotics: Science and Systems Conference, RSS 2015 - Rome, Italy
Duration: Jul 13 2015Jul 17 2015

Publication series

NameRobotics: Science and Systems
Volume11
ISSN (Electronic)2330-765X

Other

Other2015 Robotics: Science and Systems Conference, RSS 2015
Country/TerritoryItaly
CityRome
Period7/13/157/17/15

Bibliographical note

Funding Information:
This work was supported by the University of Minnesota through the Digital Technology Center (DTC), AFOSR (FA9550-10-1-0567), and the National Science Foundation (IIS-1328722).

Publisher Copyright:
© 2015, MIT Press Journals. All rights reserved.

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