吉林大学学报(信息科学版) ›› 2025, Vol. 43 ›› Issue (2): 220-230.

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基于Lidar-Iris描述子改进的LOAM算法

毛彦博a,邓荣荣b,江锦艺b,华子涵c,陈庆华b,玄玉波b   

  1. 吉林大学 a. 计算机科学与技术学院; b. 通信工程学院; c. 软件学院, 长春 130012
  • 收稿日期:2024-03-02 出版日期:2025-04-08 发布日期:2025-04-09
  • 通讯作者: 玄玉波(1979— ), 女, 长春人, 吉林大学副教授, 硕士生导师,主要从事数字图像处理、机器人工程研究,(Tel)86-13596103291(E-mail)37599218@ qq. com。 E-mail:37599218@ qq. com。
  • 作者简介:毛彦博( 2002— ), 男, 吉林通化人, 吉林大学本科生, 主要从事自动驾驶、机器人感知和控制研究, ( Tel) 86- 18904456557(E-mail)1615977891@ qq. com。
  • 基金资助:
    国家级保密军工基金资助项目(2021X024J00060)

Improved LOAM Algorithm Based on Lidar-Iris Descriptor

MAO Yanboa, DENG Rongrongb, JIANG Jinyib, HUA Zihanc, CHEN Qinghuab, XUAN Yubob   

  1. a. College of Computer Science and Technology; b. College of Communication Engineering;c. College of Software, Jilin University, Changchun 130012, China
  • Received:2024-03-02 Online:2025-04-08 Published:2025-04-09

摘要: 针对 SLAM(Simultaneous Localization and Mapping)系统在长时间运行时存在运动畸变和误差累积的问题,提出了一种基于 Lidar-Iris 构建全局描述符进行回环检测的建图方法 IRIS-LOAM(Lidar-Iris Based Lidar Odometry and Mapping in Real-Time)。 该算法在 LOAM 算法基础上, 在数据处理部分, 将激光雷达数据与 IMU( Inertial Measurement Unit)数据融合, 并使用 IMU 数据对点云数据进行校正; 在建图优化部分, 利用基于信息矩阵的图优化算法, 采用 Lidar_Iris 全局描述子对关键帧进行回环检测, 并对输入点云进行预处理, 提高优化的时间效率。 将优化算法与 A_LOAM 进行实验对比, 结果显示IRIS-LOAM在不同实地场景下都取得了较好的建图效果, 且具有良好的可行性和实用性。


关键词: 同步定位与地图构建, 激光雷达, 回环检测

Abstract: To address the issues of motion distortion and error accumulation in SLAM(Simultaneous Localization and Mapping) systems during prolonged operations, a mapping method called IRIS-LOAM ( Lidar-Iris Based Lidar Odometry and Mapping in Real-Time ) is proposed, which leverages Lidar-Iris to construct global descriptors for loop closure detection. This algorithm has two major  innovations based on the LOAM algorithm.First, in the data processing stage, it integrates lidar data with IMU(Inertial Measurement Unit) data and uses the IMU data to correct the point cloud data. Second, in the mapping optimization stage, it employs an information matrix-based graph optimization algorithm and utilizes Lidar-Iris global descriptors for loop closure detection of key frames. And it preprocesses the input point cloud to improve the time efficiency of optimization. Comparing the improved algorithm with A _ LOAM through experiments, the results show that IRIS-LOAM achieves better mapping performance in various real-world scenarios, demonstrating its feasibility and practicality.

Key words: simultaneous localization and mapping (SLAM), lidar, loop closure detection

中图分类号: 

  • TN958. 98