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A practical 2D/3D SLAM using directional patterns of an indoor structure

Authors
Lee, KeonyongRyu, Soo-HyunNam, ChangjooDoh, Nakju Lett
Issue Date
1월-2018
Publisher
SPRINGER HEIDELBERG
Keywords
Directional feature; Indoor environments; Kalman filters; Lightweight algorithm; Practical algorithm; Simultaneous localization and mapping (SLAM)
Citation
INTELLIGENT SERVICE ROBOTICS, v.11, no.1, pp.1 - 24
Indexed
SCIE
SCOPUS
Journal Title
INTELLIGENT SERVICE ROBOTICS
Volume
11
Number
1
Start Page
1
End Page
24
URI
https://scholar.korea.ac.kr/handle/2021.sw.korea/78393
DOI
10.1007/s11370-017-0234-9
ISSN
1861-2776
Abstract
This paper presents a practical two-dimensional (2D)/three-dimensional (3D) simultaneous localization and mapping (SLAM) algorithm using directional features for ordinary indoor environments; this algorithm is adaptable to various conditions, computationally inexpensive, and accurate enough to use for practical applications. The proposed algorithm uses odometry acquired from other sensors or other algorithms as the initial estimate and the directional features of indoor structures as landmarks. The directional features can only correct the rotation error of the odometry. However, we show that the greater part of the translation error of the odometry can also be corrected when the directional features are detected at almost positions accurately. In that case, there is no need to use other kinds of features to correct translation error. The directions of indoor structures have two advantages as landmarks. First, the extraction of them is not affected by obstacles. Second, the number of them is small regardless of the size of the building. Because of these advantages, the proposed SLAM algorithm shows robustness for parameters and lightweight properties. From extensive experiments with 2D/3D datasets taken from different buildings, we show the practicality of the proposed algorithm. We also demonstrate that the 2D algorithm runs in real time on a low-end smartphone.
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