基于无人机视觉的船舶靠泊距离感知研究
DOI:
CSTR:
作者:
作者单位:

大连海事大学

作者简介:

通讯作者:

中图分类号:

U675.9;TN98

基金项目:

国家自然科学基金项目(重点项目:52231014)


Research on ship berthing distance perception based on UAV vision
Author:
Affiliation:

Fund Project:

  • 摘要
  • |
  • 图/表
  • |
  • 访问统计
  • |
  • 参考文献
  • |
  • 相似文献
  • |
  • 引证文献
  • |
  • 资源附件
  • |
  • 文章评论
    摘要:

    为解决船舶靠泊过程中视野受限问题,实现靠泊距离的可视化,提出了一种基于无人机视觉的靠泊距离感知方法。首先,利用无人机采集船舶靠泊视频,在YOLOv8分割模型的基础上加入EMA注意力机制,实现对船舶边缘的精细化分割;接下来,通过区域生长算法和霍夫直线检测方法提取泊位线;最后,利用最近距离求解模型,将船舶和泊位转换到三维世界坐标系中,并搜索船舶与泊位间的最近距离。实验结果表明,加入EMA注意力机制后的算法对船舶分割的精度可达到92.3%,船舶与泊位间最近距离的误差小于0.1m。该方法不仅可以监控靠泊船舶周围的环境,而且能够实现船舶与泊位间距离的可视化,在靠泊操作中具有很好的应用前景。

    Abstract:

    In order to solve the problem of limited field of view during ship berthing and achieve the visualization of berthing distance, a berthing distance perception method based on UAV vision is proposed. First, the UAV is used to collect the berthing video of the ship, and the EMA mechanism is added on the basis of the YOLOv8 segmentation model to achieve the fine segmentation of the ship edges. Next, the berth line is extracted by the regional growth algorithm and the Hough line detection. Finally, the closest distance calculation model is used to convert ships and berths into three-dimensional world coordinate system, and the closest distance between ships and berths is searched. The experimental results show that the accuracy of the algorithm after adding the EMA attention mechanism can reach 92.3% of the segmentation accuracy, and the error of the closest distance between the ship and the berth is less than 0.1m. This method can not only monitor the environment around the berthing ship, but also achieve the visualization of the distance between the ship and the berth, which has a good application prospect in berthing operation.

    参考文献
    相似文献
    引证文献
引用本文
分享
文章指标
  • 点击次数:
  • 下载次数:
  • HTML阅读次数:
  • 引用次数:
历史
  • 收稿日期:2024-10-13
  • 最后修改日期:2024-12-17
  • 录用日期:2024-12-18
  • 在线发布日期:
  • 出版日期:
文章二维码
×
《电子测量技术》
财务封账不开票通知