A Square Root Inverse Filter for Efficient Vision-aided Inertial Navigation on Mobile Devices

被引:0
|
作者
Wu, Kejian J. [1 ]
Ahmed, Ahmed M. [2 ]
Georgiou, Georgios A. [2 ]
Roumeliotis, Stergios, I [2 ]
机构
[1] Univ Minnesota, Dept Elect & Comp Engn, Minneapolis, MN 55455 USA
[2] Univ Minnesota, Dept Comp Sci & Engn, Minneapolis, MN USA
基金
美国国家科学基金会;
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暂无
中图分类号
TP24 [机器人技术];
学科分类号
080202 ; 1405 ;
摘要
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.
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页数:9
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