您好，欢迎访问北京市农林科学院 机构知识库！
北京市农林科学院机构知识库

全部

  • 全部
  • 标题
  • 学者
  • 机构
  • 关键词

Three-dimensional trajectory extraction and flower structure coupling method for bee-flower interactions

文献类型： 外文期刊

作者： Leng, Ying 1 ; Feng, Shuaiqi 1 ; Zhong, Ziyi 1 ; Wu, Sheng 2 ; Guo, Minkun 3 ; Wen, Weiliang 2 ; Xu, Jian 1 ;

作者机构： 1.Beijing Univ Agr, Coll Intelligent Sci & Engn, Beijing 102206, Peoples R China

2.Beijing Acad Agr & Forestry Sci, Informat Technol Res Ctr, Beijing 100097, Peoples R China

3.Natl Engn Res Ctr Informat Technol Agr, Beijing Key Lab Digital Plant, Beijing 100097, Peoples R China

关键词： Nectar guides; Three-dimensional; Trajectory; Floral structure; mu-CT; Ultraviolet; RGB-D vision

期刊名称：COMPUTERS AND ELECTRONICS IN AGRICULTURE （ 影响因子：8.9； 五年影响因子：9.3 ）

ISSN： 0168-1699

年卷期： 2025 年 238 卷

页码：

收录情况： SCI

摘要： Understanding the spatial relationship between bee flower-visiting trajectories and floral structures is critical for elucidating pollination guidance mechanisms and improving pollination strategies. However, existing studies generally lack systematic analysis of the dynamic coupling between flight trajectories and floral structures, largely due to limitations in high-precision trajectory acquisition and structural reconstruction. This study proposes a multimodal perception framework that combines micro-computed tomography (mu-CT), ultraviolet (UV) imaging, and RGB-D vision to build a high-resolution 3D bee flight trajectory tracking system. A convolutional block attention module (CBAM) is incorporated into the YOLOv8 network to detect bee head and body positions, achieving a mean trajectory reconstruction error of 0.49 mm. UV images are used to generate pseudo3D point clouds of nectar guide graphs, which are spatially registered with floral models reconstructed via mu-CT scanning. Multi-source point cloud alignment is performed using principal component analysis (PCA), random sample consensus (RANSAC), and iterative closest point (ICP) algorithms. Trajectory analysis shows that approximately 50.3 % of bee stopping points are concentrated in reproductive organs, highlighting these as core regions of interaction. Nectar guides accounted for 20.3 % of stopping points, suggesting their role in spatial navigation and localization. To the best of our knowledge, this is the first study to achieve high-resolution fusion of bee flight trajectories with detailed floral structures. The proposed approach provides a technical basis for modeling the integrated process of perception, decision-making, behavioral adjustment, and structural interaction, while offering data support for precision pollination strategies and the development of bioinspired systems.

  • 相关文献
作者其他论文 更多>>
置顶
购物车
反馈

© 京ICP备09089781号-29 主办单位：北京市农林科学院

学术资源： 中国农业科学院 农业专业知识服务系统 农科联盟资源共建共享平台 中国农业科技文献与信息服务平台 中国农业期刊集成服务平台