Application of optimal configuration-based line features in indoor RGB-D SLAM system

被引：0
|
作者：
Xia L. [1 ]
Cui J. [1 ]
Song Z. [1 ]
Hu Y. [1 ]
Hu Z. [1 ]
机构：
[1] School of Automation Engineering, Northeast Electric Power University, Jilin
来源：
Zhongguo Guanxing Jishu Xuebao/Journal of Chinese Inertial Technology | 2022年 / 30卷 / 06期
关键词：
Factor graph; Feature primitives; Indoor RGB-D SLAM; Line feature configuration; Pose estimation;
D O I：
10.13695/j.cnki.12-1222/o3.2022.06.009
中图分类号：
学科分类号：
摘要：
Motion estimation is the core problem of visual simultaneous localization and mapping (SLAM) studies. Starting from the extraction, matching (association) and parameterization of geometric-object feature primitives, combined with factor graph optimization, the indoor RGB-D SLAM system framework is constructed. The strategy of 'optimal configuration of line features' has been applied to the point-line-plane constraints fused pose estimation, and the number of optimal line feature extraction is determined in terms of benchmark ICL-NUIM and TUM dataset tests. The localization robustness under weakly textured scenes, as well as the result interpretability, is therefore enhanced. The comparative tests on ORB-SLAM2, PL-SLAM and SP-SLAM illustrate that the proposed design exhibits the best global localization results. When compared to SP-SLAM, the proposed method leads to a 4.33% increase of trajectory estimation accuracy on 8 sub sequences of ICL-NUIM dataset and a 21.40% increase of trajectory estimation accuracy on 4 sub sequences of TUM dataset respectively. © 2022, Editorial Department of Journal of Chinese Inertial Technology. All right reserved.
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页码：760 / 767and776
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