吉林大学学报(工学版) ›› 2023, Vol. 53 ›› Issue (8): 2395-2403.doi: 10.13229/j.cnki.jdxbgxb.20211090

• 通信与控制工程 • 上一篇    

基于点云直方图的回环检测算法和车辆定位方法

李寿涛1(),李嘉霖1,2,孟庆瑜1,2,郭洪艳1,2()   

  1. 1.吉林大学 通信工程学院，长春 130022
    2.吉林大学 汽车仿真与控制国家重点实验室，长春 130022
  • 收稿日期:2021-10-23 出版日期:2023-08-01 发布日期:2023-08-21
  • 通讯作者: 郭洪艳 E-mail:list@jlu.edu.cn;guohy11@jlu.edu.cn
  • 作者简介:李寿涛（1975-），男，副教授，博士. 研究方向：车辆稳定性控制.E-mail：list@jlu.edu.cn
  • 基金资助:
    国家自然科学基金区域创新发展联合基金项目(U19A2069);吉林省科技厅重大科技项目专项子课题(20200501011GX);吉林省科技发展计划重点研发项目(20200401088GX)

Loop-closure detection algorithm based on point cloud histogram and vehicle positioning method

Shou-tao LI1(),Jia-lin LI1,2,Qing-yu MENG1,2,Hong-yan GUO1,2()   

  1. 1.College of Communication Engineering，Jilin University，Changchun 130022，China
    2.State Key Laboratory of Automotive Simulation and Control，Jilin University，Changchun 130022，China
  • Received:2021-10-23 Online:2023-08-01 Published:2023-08-21
  • Contact: Hong-yan GUO E-mail:list@jlu.edu.cn;guohy11@jlu.edu.cn

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摘要：

针对智能车辆在城市复杂路段由于全球定位系统GPS信号丢失导致的定位失准问题，建立因子图优化模型对激光雷达和惯性测量单元进行数据融合，提出一种紧耦合框架下的激光-惯性里程计（LIO）车辆定位方法，实时估计车辆状态信息；并提出基于点云直方图的回环检测算法，通过计算车辆当前位置与历史时刻位置间点云的相似度判断车辆是否到达同一位置，进而结合上一次经过该位置时的信息校正车辆当前状态，减少定位误差的积累。KITTI数据集上的测试结果表明：回环检测模块可有效降低LIO的误差积累，带有回环检测模块的LIO具备良好的定位精度。

关键词: 控制科学与工程, 点云直方图, 回环检测, 车辆定位

Abstract:

Aiming at the problem of inaccurate positioning of intelligent vehicles due to the loss of GPS signals on complex urban roads， a factor graph optimization model is established to perform data fusion on LiDAR （Light detection and ranging） and Inertial Measurement Unit（IMU）， and the lidar-inertial odometry （LiDAR-inertial odometry， LIO） vehicle positioning method under the tightly-coupled framework is proposed， which can estimate vehicle state information in real time； a loop-closure detection algorithm based on point cloud histograms is proposed. The similarity of the point cloud determines whether the vehicle has reached the same position， and then combines the information from the last time that the vehicle passed the position to correct the current state of the vehicle， reducing the accumulation of positioning errors. The test results on the KITTI dataset show that the loop-closure detection module can effectively reduce the error accumulation of the LIO， and the LIO with the loop-closure detection module has excellent positioning accuracy.

Key words: control science and engineering, point cloud histogram, loop-closure detection, vehicle positioning

中图分类号: 

  • TP391.4

图1

系统框图"

图2

运动补偿原理"

图3

IMU预积分原理"

图4

滑动窗口运行策略"

图5

胞元的分类"

图6

05序列各系统轨迹对比"

图7

05序列LIO-loop轨迹误差"

图8

车辆第一次经过点A时的点云直方图"

图9

车辆第二次经过点A时的点云直方图"

图10

05序列LIO-loop轨迹绝对位置误差统计数据"

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