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)|
|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|
|State||Published - 2015|
|Event||2015 Robotics: Science and Systems Conference, RSS 2015 - Rome, Italy|
Duration: Jul 13 2015 → Jul 17 2015
|Name||Robotics: Science and Systems|
|Other||2015 Robotics: Science and Systems Conference, RSS 2015|
|Period||7/13/15 → 7/17/15|
Bibliographical noteFunding 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).
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