上海交通大学学报

上海交通大学学报 >

2022 , Vol. 56 >Issue 10: 1379 - 1387

DOI: https://doi.org/10.16183/j.cnki.jsjtu.2021.202

机械与动力工程

基于全局特征描述子的激光SLAM回环检测方法

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  • 1.上海交通大学 机械与动力工程学院,上海 200240
    2.中煤科工集团上海有限公司,上海 201100
韩 超(1997-),男,浙江省宁波市人,硕士生,主要从事井下无人机定位技术研究.

收稿日期: 2021-06-11

  网络出版日期: 2022-11-03

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Loop Closure Detection Method of Laser SLAM Based on Global Feature Descriptor

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  • 1. School of Mechanical Engineering, Shanghai Jiao Tong University, Shanghai 200240, China
    2. China Coal Technology and Engineering Group Shanghai Co., Ltd., Shanghai 201100, China

Received date: 2021-06-11

  Online published: 2022-11-03

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摘要

针对井下环境中设备巡检时定位误差随时间不断累积的问题,提出一种适用于激光同步定位和建图技术的基于点云全局特征描述子的回环检测方法.该方法利用曲率计算点云中特征点的特征向量,通过特征向量与中心点坐标系的角度分布和尺度分布关系构建点云全局特征描述子;使用部分特征点进行位姿变换的计算,提高计算效率.通过仿真实验和开源数据集实验对所提算法进行验证.实验结果表明,所提算法在定位精度和实时性上提升明显,可以有效解决定位算法在长时间运行过程中的累积误差和全局一致性差的问题.

关键词： 井下巡检; 激光定位; 回环检测; 全局特征描述子

本文引用格式

韩超, 陈敏, 黄宇昊, 赵明辉, 杜乾坤, 梁庆华 . 基于全局特征描述子的激光SLAM回环检测方法[J]. 上海交通大学学报, 2022 , 56(10) : 1379 -1387 . DOI: 10.16183/j.cnki.jsjtu.2021.202

Abstract

To solve the problem that localization error of the underground inspection system continues to accumulate over time, a loop closure detection algorithm based on point cloud global feature descriptor is proposed, which is suitable for laser simultaneous localization and mapping (SLAM). The feature vector of each point in point cloud is calculated by curvature, then the global feature descriptor of point cloud is constructed based on the angle distribution and scale distribution relationship between the feature vector and center point coordinate system. In addition, the pose transformation of two similar frames is calculated by feature point registration to improve computing efficiency. The proposed algorithm is verified by simulation experiments and open-source data experiments. The experimental results show that the proposed algorithm has a significant improvement in localization accuracy and real-time performance, which can effectively solve the problems of increased cumulative error and poor global consistency of the localization algorithm during long-term inspections.

Key words： underground inspection; laser localization; loop closure detection; global feature descriptor

参考文献

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