Improved 2D laser slam graph optimization based on Cholesky decomposition

Liangliang Gao, Chaoyi Dong, Xiaoyang Liu, Qifan Ye, Kang Zhang, Xiaoyan Chen
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引用次数: 1

Abstract

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.
基于Cholesky分解的改进二维激光冲击图优化
在急转弯、快速运动、计算时间有限等特定场景中,激光slam通常需要以较快的速度完成后端图形优化。针对这些问题,本文提出了一种结合Cholesky分解的二维激光slam后端图优化方法来加速线性求解过程,从而达到加速图优化的目的。在MATLAB仿真实验中,与不进行Cholesky分解的传统方法相比,结合Cholesky分解的二维激光slam后端图优化率提高了24%。实验结果验证了改进方法的有效性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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