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) |
|---|---|
| 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 |
|---|---|
| Volume | 11 |
| ISSN (Electronic) | 2330-765X |
Other
| Other | 2015 Robotics: Science and Systems Conference, RSS 2015 |
|---|---|
| Country/Territory | Italy |
| City | Rome |
| Period | 7/13/15 → 7/17/15 |
Bibliographical note
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