您好,欢迎访问北京市农林科学院 机构知识库!

Design of structured-light vision system for tomato harvesting robot

文献类型: 外文期刊

作者: Feng Qingchun 1 ; Cheng Wei 2 ; Zhou Jianjun 1 ; Wang Xiu 1 ;

作者机构: 1.Beijing Res Ctr Intelligent Equipment Agr, Beijing 100097, Peoples R China

2.Zhejiang Univ Technol, Hangzhou 100085, Zhejiang, Peoples R China

关键词: harvesting robot;tomato;linear structure-light;3D measurement;feature extraction

期刊名称:INTERNATIONAL JOURNAL OF AGRICULTURAL AND BIOLOGICAL ENGINEERING ( 影响因子:2.032; 五年影响因子:2.137 )

ISSN: 1934-6344

年卷期: 2014 年 7 卷 2 期

页码:

收录情况: SCI

摘要: In order to improve the operating precision of the harvesting robot, a vision system for intelligently identifying and locating the mature tomato was designed. The active detection method based on structured-light stereo vision was expected to deal with the problem of variable illumination and target occlusion in the glasshouse. The maximum between-cluster variances of hue (H) and saturation (S) value were adopted as the threshold for color segmentation, which weakened the impact on the image caused by the light intensity variation. Through the limit on the pixel size and circularity of the candidate areas, the vision system recognized the fruit area and removed the noise areas. The fruit's 3D position was computed on the basis of spatial relationship between the laser plane and the camera, when the linear laser was projected on the centre area of the mature fruit. The blue view-scanning laser stripe pixels on the mature fruit were extracted according to its Cb color characteristic. As the field test results show, the measurement error on the fruit radius is less than 5 mm, the centre distance error between the fruit and camera is less than 7 mm, and the single axis coordinate error is less than 5.6 mm. This structured-light vision system could effectively identify and locate mature fruit.

  • 相关文献

[1]Design and Test of Tomatoes Harvesting Robot. Feng, Qingchun,Wang, Xiaonan,Wang, Guohua,Li, Zhen. 2015

[2]Design and test of robotic harvesting system for cherry tomato. Feng, Qingchun,Feng, Qingchun,Feng, Qingchun,Zou, Wei,Zou, Wei,Zou, Wei,Fan, Pengfei,Zhang, Chunfeng,Fan, Pengfei,Zhang, Chunfeng,Fan, Pengfei,Zhang, Chunfeng,Wang, Xiu,Wang, Xiu,Wang, Xiu. 2018

[3]Vertical features of yellow rust infestation on winter wheat using hyperspectral imaging measurements. Zhao, Jinling,Zhang, Dongyan,Huang, Linsheng,Zhang, Qing,Liu, Wenjing,Yang, Hao. 2016

[4]Geographical classification of apple based on hyperspectral imaging. Guo, Zhiming,Huang, Wenqian,Chen, Liping,Zhao, Chunjiang. 2013

[5]Establishment and Application of Ty-2 Molecular Marker in Tomatoes. Ruixing Yatng,Shuwen lv,Min Chai,Haitao Li. 2012

[6]Determining the Dominant Environmental Parameters for Greenhouse Tomato Seedling Growth Modeling Using Canonical Correlation Analysis. Q. Qiu,K. Shi,X. J. Qiao,K. Jiang. 2016

[7]Establishment and Application of Ty-2 Molecular Marker in Tomatoes. Yang, Ruixing,Li, Haitao,Lv, Shuwen,Li, Haitao,Chai, Min. 2012

[8]Design of End-effector for Tomato Robotic Harvesting. Wang, Guohua,Yu, Yabo,Feng, Qingchun. 2016

[9]Residue behavior and dietary intake risk assessment of three fungicides in tomatoes (Lycopersicon esculentum Mill.) under greenhouse conditions. Zhu, Xiaodan,Jia, Chunhong,Yu, Pingzhong,He, Min,Chen, Li,Zhao, Ercheng,Duan, Lifang,Zhang, Wei. 2016

[10]Determining the Dominant Environmental Parameters for Greenhouse Tomato Seedling Growth Modeling Using Canonical Correlation Analysis. Qiu, Q.,Qiao, X. J.,Jiang, K.,Shi, K.. 2016

[11]Tomato Leaf Liriomyza Sativae Blanchard Pest Detection Based on Hyperspectral Technology. Li Cui-ling,Jiang Kai,Ma Wei,Wang Xiu,Meng Zhi-jun,Zhao Xue-guan,Song Jian,Li Cui-ling,Jiang Kai,Ma Wei,Wang Xiu,Meng Zhi-jun,Zhao Xue-guan,Song Jian. 2018

[12]Comparison of Coconut Coir, Rockwool, and Peat Cultivations for Tomato Production: Nutrient Balance, Plant Growth and Fruit Quality. Xiong, Jing,Wang, Jingguo,Chen, Qing,Xiong, Jing,Liu, Wei,Tian, Yongqiang. 2017

[13]Small RNAs were involved in homozygous state-associated silencing of a marker gene (Neomycin phosphotransferase II: NptII) in transgenic tomato plants. Deng, Lei,Pan, Yu,Chen, Guoping,Hu, Zongli,Chen, Xuqing.

[14]Gene expression analyses of ZmPti1, encoding a maize Pti-like kinase, suggest a role in stress signaling. Zou, HW,Wu, ZY,Yang, Q,Zhang, XH,Cao, MQ,Jia, WS,Huang, CL,Xiao, X.

[15]Maize Leaf Biomass Retrieval at Multi-growing Stage Using UAV Multispectral Images Based on 3D Radiative Transfer Process-guided Machine Learning. Dan Zhao,Hao Yang,Guijun Yang,Xingang Xu,Bo Xu. 2024

[16]A Method for Counting Leaves of Cabbage Seedlings Based on Instance Segmentation. Ning Zhang,Huarui Wu,Huaji Zhu,Yisheng Miao,Xiang Sun. 2022

[17]Enhancing Outdoor Fruit Localization Accuracy: A Stereo Network Approach with Parallax Attention. Feng Xie,Tao Li. 2023

[18]Segmentation and Extraction of Maize Phytomers Using 3D Data Acquired by RGB-D Cameras. Zhengqiang Fan,Na Sun,Jian Xu,Tao Li,Quan Qiu. 2023

作者其他论文 更多>>