Improved algorithm of cartographer based on laser odometer

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Abstract

In the front-end matching process of the Cartographer algorithm, the accuracy of matching between the point cloud and submap relies on the initial values provided by the pose fusion algorithm. However, the original algorithm's pose fusion algorithm has low accuracy. To address this issue, this paper proposes an improved Cartographer algorithm based on a laser odometer. The improved algorithm utilizes NDT registration to obtain the pose transformation between frames. Additionally, a pre-integration of the IMU between the front and back frames is performed for joint optimization, allowing for the acquisition of a more accurate pose. This enhanced accuracy contributes to improving the matching of high point clouds with the submap. To analyze the efficacy of the improved algorithm, comparisons were made with the original Cartographer algorithm by analyzing the map construction effect and conducting positioning accuracy tests using datasets. The experiments confirmed that the improved algorithm is both feasible and effective in enhancing the map construction effect and pose accuracy.
基于激光里程计的制图改进算法
在Cartographer算法的前端匹配过程中,点云和子地图的匹配精度依赖于姿态融合算法提供的初始值。然而,原算法的姿态融合算法精度较低。为了解决这一问题,本文提出了一种基于激光里程计的改进制图算法。改进算法利用无损检测配准获得帧间的姿态变换。此外,在前后框架之间进行IMU的预集成,以进行关节优化,从而获得更准确的姿势。这种提高的精度有助于改善高点云与子地图的匹配。为了分析改进算法的有效性,通过分析地图构建效果和使用数据集进行定位精度测试,将改进算法与原Cartographer算法进行对比。实验验证了改进算法在提高地图构建效果和姿态精度方面的可行性和有效性。
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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