Improved 2D laser slam graph optimization based on Cholesky decomposition

被引:0
|
作者
Gao, Liangliang [1 ,2 ]
Dong, Chaoyi [1 ,2 ]
Liu, Xiaoyang [1 ,2 ]
Ye, Qifan [1 ,2 ]
Zhang, Kang [1 ,2 ]
Chen, Xiaoyan [1 ,2 ]
机构
[1] Inner Mongolia Univ Technol, Coll Elect Power, Hohhot 010080, Peoples R China
[2] Intelligent Energy Technol & Equipment Engn Res C, Hohhot 010051, Peoples R China
基金
中国国家自然科学基金;
关键词
D O I
10.1109/CODIT55151.2022.9803938
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Laser slam usually needs to complete a back-end graph optimization at a fast speed in some specific scenes, such as sharp turns, fast motion, and limited calculation time. Aiming at these problems, this paper proposed a 2D laser slam back-end graph optimization combined with Cholesky decomposition to accelerate a linear solution process and further to achieve a purpose of accelerating graph optimization. In MATLAB simulation experiments, the rate of 2D laser slam back-end graph optimization combined with Cholesky decomposition increased 24%, compared to that of the traditional method without Cholesky decomposition. The result verified the effectiveness of the improved method.
引用
收藏
页码:659 / 662
页数:4
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