农业机械学报2026，Vol.57Issue(1)：19-29,11.DOI:10.6041/j.issn.1000-1298.2026.01.002
基于环绕式无人车表型平台和同源传感阵列的田间原位表型数据融合解析方法
Method for Fusion Analysis of In-situ Field Phenotyping Data Based on Surrounding Unmanned Vehicle Phenotyping Platform and Homologous Sensor Arrays
摘要
Abstract
High-throughput and precise acquisition and analysis of crop phenotypic information are fundamental components of modern agricultural breeding and precision cultivation systems.However,traditional manual measurements in complex field environments are limited by low efficiency,high labor intensity,and strong subjectivity,making it difficult to meet the growing demand for large-scale,multi-trait,and time-series phenotyping.To address these challenges,an in-field phenotypic data fusion and analysis method was proposed based on a ring-shaped unmanned vehicle phenotyping platform and a multimodal homogeneous sensor array.The platform integrated multiple homogeneous sensors,including RGB and depth cameras,enabling multi-angle and three-dimensional in situ crop observations.A systematic multi-source heterogeneous data fusion workflow was designed,consisting of image preprocessing,depth information extraction,3D reconstruction,temporal tracking,and feature analysis,to achieve accurate extraction and dynamic reconstruction of key phenotypic traits such as plant height,canopy structure,and spatial distribution.Field experiments were conducted on maize plants at multiple growth stages.The results demonstrated that the proposed platform can stably and continuously acquire high-quality multimodal phenotypic data.The reconstructed plant height measurements showed a high correlation with manual measurements,with an average error within 5 cm,verifying the accuracy and robustness of the method.Compared with conventional single-view or mechanically rotating observation methods,the proposed platform exhibited superior adaptability to field environments,allowing rapid deployment and efficient operation,thereby providing an effective technical foundation for large-scale in-field phenotyping.Furthermore,the platform's advantages were discussed in terms of portability,scalability,timeliness,and automation,and envisions future developments toward embodied intelligence and autonomous phenotyping.The proposed ring-type unmanned vehicle platform and multimodal data fusion method can provide a high-throughput,low-disturbance,and scalable technical solution for in-field crop phenomics,supporting modern crop breeding and precision agriculture.关键词
玉米/作物表型/无人车平台/多模态传感/数据融合/三维重建Key words
maize/crop phenotyping/unmanned vehicle platform/multimodal sensing/data fusion/3D reconstruction分类
信息技术与安全科学引用本文复制引用
LI Yinglun,CAI Shichen,ZHANG Yanyu,ZHU Yongji,MA Ruitao,FAN Jiangchuan,GUO Xinyu..基于环绕式无人车表型平台和同源传感阵列的田间原位表型数据融合解析方法[J].农业机械学报,2026,57(1):19-29,11.基金项目
国家自然科学基金项目(32330075)、国家重点研发计划项目(2022YFD2002300)和北京市农林科学院协同创新中心建设项目(KJCX20240406) （32330075）
