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基于改进关键帧选择的ORB-SLAM2算法

张洪 于源卓 邱晓天

张洪,于源卓,邱晓天. 基于改进关键帧选择的ORB-SLAM2算法[J]. 北京航空航天大学学报,2023,49(1):45-52 doi: 10.13700/j.bh.1001-5965.2021.0173
引用本文: 张洪,于源卓,邱晓天. 基于改进关键帧选择的ORB-SLAM2算法[J]. 北京航空航天大学学报,2023,49(1):45-52 doi: 10.13700/j.bh.1001-5965.2021.0173
ZHANG H,YU Y Z,QIU X T. ORB-SLAM2 algorithm based on improved key frame selection[J]. Journal of Beijing University of Aeronautics and Astronautics,2023,49(1):45-52 (in Chinese) doi: 10.13700/j.bh.1001-5965.2021.0173
Citation: ZHANG H,YU Y Z,QIU X T. ORB-SLAM2 algorithm based on improved key frame selection[J]. Journal of Beijing University of Aeronautics and Astronautics,2023,49(1):45-52 (in Chinese) doi: 10.13700/j.bh.1001-5965.2021.0173

基于改进关键帧选择的ORB-SLAM2算法

doi: 10.13700/j.bh.1001-5965.2021.0173
详细信息
    通讯作者:

    E-mail:zhanghong@jiangnan.edu.cn

  • 中图分类号: TP242.6

ORB-SLAM2 algorithm based on improved key frame selection

More Information
  • 摘要:

    针对同时定位与建图(SLAM)算法精度不高且跟踪易失败的问题,提出了一种改进关键帧选择的ORB-SLAM2算法。通过ORB-SLAM2算法计算帧间相对位姿;在原有算法的基础上,增加旋转与平移量作为判定依据,决定是否创建新关键帧;针对移动机器人所安装的相机与机器人产生相对运动引发误拍摄,导致劣质关键帧生成的问题,设计了劣质关键帧剔除算法;基于RGB-D数据集与自主研发的移动机器人进行了实验验证。实验结果表明:改进的关键帧选择算法能够准确及时地选择关键帧,最优情况下定位误差约为原误差的51.9%,有效消除了相机与机器人之间相对运动产生的影响,直线误差仅为原误差的82.1%。改进算法能够有效提高定位精度,减少跟踪失败。

     

  • 图 1  关键帧选取示意图

    Figure 1.  Schematic of key frame selection

    图 2  关键帧选择算法流程

    Figure 2.  Flowchart of key frame selection algorithm

    图 3  三种关键帧选择算法运动轨迹对比

    Figure 3.  Comparison of motion trajectories of three key frame selection algorithms

    图 4  定位轨迹误差曲线

    Figure 4.  Curve of track positioning error

    图 5  数据集实验关键帧数量比较

    Figure 5.  Comparison of key frame numbers in dataset experiments

    图 6  移动机器人

    Figure 6.  Mobile robot

    图 7  回环运动轨迹对比

    Figure 7.  Comparison of loop trajectories

    图 8  移动机器人实验关键帧数量比较

    Figure 8.  Comparison of key frame numbers in mobile robot experiments

    表  1  平均跟踪时间对比结果

    Table  1.   Comparison of mean tracking time

    数据集平均跟踪时间/ms
    常用关键帧
    选择算法
    包含劣质关键
    帧的改进算法
    剔除劣质关键
    帧的改进算法
    desk394551
    xyz465157
    room303136
    下载: 导出CSV

    表  2  最大绝对轨迹误差对比

    Table  2.   Maximum absolute trajectory error

    数据集最大绝对轨迹误差/m
    常用关键帧
    选择算法
    包含劣质关键
    帧的改进算法
    剔除劣质关键
    帧的改进算法
    desk0.1310.0640.062
    xyz0.1240.0970.097
    room0.2020.1250.130
    下载: 导出CSV

    表  3  平均位置误差

    Table  3.   Average position error

    运动方式平均位置误差/m
    常用关键帧
    选择算法
    包含劣质关键
    帧的改进算法
    剔除劣质关键
    帧的改进算法
    直线0.2090.2020.164
    转弯0.9640.5650.543
    回环1.2360.7320.721
    下载: 导出CSV
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出版历程
  • 收稿日期:  2021-04-06
  • 录用日期:  2021-05-14
  • 网络出版日期:  2023-01-16
  • 刊出日期:  2021-05-26

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