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 language | English (US) |
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Title of host publication | Robotics |
Subtitle of host publication | Science and Systems XI, RSS 2015 |
Editors | Jonas Buchli, David Hsu, Lydia E. Kavraki |
Publisher | MIT Press Journals |
ISBN (Electronic) | 9780992374716 |
DOIs | |
State | Published - 2015 |
Event | 2015 Robotics: Science and Systems Conference, RSS 2015 - Rome, Italy Duration: Jul 13 2015 → Jul 17 2015 |
Publication series
Name | Robotics: Science and Systems |
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Volume | 11 |
ISSN (Electronic) | 2330-765X |
Other
Other | 2015 Robotics: Science and Systems Conference, RSS 2015 |
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Country | Italy |
City | Rome |
Period | 7/13/15 → 7/17/15 |
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).