Research on backend optimization of SLAM based on PageRank

被引：0
|
作者：
Zhang J. [1 ]
Zhang H. [1 ]
Liu X. [1 ]
机构：
[1] School of Mechanical Engineering, Hebei University of Technology, Tianjin
来源：
Huazhong Keji Daxue Xuebao (Ziran Kexue Ban)/Journal of Huazhong University of Science and Technology (Natural Science Edition) | 2019年 / 47卷 / 04期
关键词：
Backend optimization; Node sorting; PageRank; Simultaneous localization and mapping (SLAM); Sparse;
D O I：
10.13245/j.hust.190411
中图分类号：
学科分类号：
摘要：
A fast method based on PageRank for the simultaneous localization and mapping (SLAM) was presented to address the problem of indoor complex and non-institutional environment mapping and low positioning efficiency. In the indoor complex unstructured environment, the pose graph created by the SLAM frontend contained a large number of nodes to be optimized. According to the sparse matrix created by the SLAM backend, the PageRank algorithm was used to filter and sort the nodes in the pose graph, and the nodes below the set threshold were removed from the graph, and the nodes with high correlation with other nodes were kept. The method reduced the nodes in the pose graph and retained the sparse characteristics of the SLAM backend, thus, SLAM backend optimization efficiency was improved. Experimental results were verified on the RGB-D standard dataset, which shows that the proposed SLAM backend optimization algorithm shortens the optimization time and improves the real-time performance in the indoor environment, and the error variation is within the acceptable range. The proposed method provides a solution to the problem of SLAM backend optimization in efficiency. © 2019, Editorial Board of Journal of Huazhong University of Science and Technology. All right reserved.
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页码：61 / 66
页数：5
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