skip to main content
10.1145/3627341.3630401acmotherconferencesArticle/Chapter ViewAbstractPublication PagesiccvitConference Proceedingsconference-collections
research-article

Research on Target Localization of Automatic Picking Robot for Rock Sugar Orange

Published: 15 December 2023 Publication History

Abstract

In the production process of rock sugar oranges, picking is the most labor-intensive step. Intelligent replacement of traditional manual labor, timely and rapid picking of rock sugar oranges, improving fruit picking quality, is of great significance for expanding the rock sugar orange market. How to effectively recognize and locate rock sugar oranges is a key technology in machine vision in the research of automatic picking robots. A rock sugar orange positioning method is proposed. Firstly, the rock sugar orange image is preprocessed, binarized using Otsu adaptive threshold segmentation, and the positioning parameters and radius of the rock sugar orange are obtained using Hough transform. The K-means clustering pattern classification method is used to classify different circles, and the clustering results are corrected using a circle parameter correction model.

References

[1]
Wu Hongjie, Zhang Yuehui, Wang Zheng, Overview of Robot Development in Japan [J]. Electronic Production, 2013 (09): 245-248
[2]
Wang Rujing, Sun Bingyu. Development Status and Prospect of agricultural robot [J]. Journal of the Chinese Academy of Sciences, 2015, 030 (006): 803-809
[3]
Schertz, C E, Brown G K. Basic considerations in mechanizing citrus Harvest [J] Transactions of the ASAE, 1968, 11 (2): 343-346
[4]
Cheng Fang, Wu Wenxiu, He Han, Research on target recognition and localization methods for citrus picking robots [J]. Science and Technology Information, 2019,17 (11): 30-31
[5]
Liu, Tian, Ehsani R, Toudeshki, Detection of citrus fruit and tree trunks in natural environments using a multi-elliptical boundary model[J].Computers in Industry 2018,99(12):9-16.
[6]
Kaimin, G. Tianshi, C. Zhen, Z, Research on tomato-harvesting robot visual system[J],. Journal of Agricultural Mechanization Research.2016,12(6):218-214
[7]
GONG Pingshun,HONG yan.Real-time displacement feedback method of mine similar simulation field based on multi-circle detection[J],Journal of North China Institute of Science and Technology,2022,19(3):54-60.
[8]
WEI Wenda ZHANG Bin.Multi-circle Detection in Automatic Measurement of Brinell Hardness[J],Compute&Digital Engineering,2021,49(3):567-572.
[9]
Chen Liwei, Liu Susu1,Yuan Hui, Qu Chang,et al.Saw chain image segmentation algorithm fusion assembly
[10]
features and regression analysi[J],Electronic Measurement Technology,2022,45(12):139-145.

Index Terms

  1. Research on Target Localization of Automatic Picking Robot for Rock Sugar Orange
        Index terms have been assigned to the content through auto-classification.

        Recommendations

        Comments

        Information & Contributors

        Information

        Published In

        cover image ACM Other conferences
        ICCVIT '23: Proceedings of the 2023 International Conference on Computer, Vision and Intelligent Technology
        August 2023
        378 pages
        ISBN:9798400708701
        DOI:10.1145/3627341
        Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than the author(s) must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected].

        Publisher

        Association for Computing Machinery

        New York, NY, United States

        Publication History

        Published: 15 December 2023

        Permissions

        Request permissions for this article.

        Check for updates

        Author Tags

        1. Gradient Hough transform
        2. Machine vision
        3. Threshold segmentation
        4. target location

        Qualifiers

        • Research-article
        • Research
        • Refereed limited

        Conference

        ICCVIT 2023

        Acceptance Rates

        ICCVIT '23 Paper Acceptance Rate 54 of 142 submissions, 38%;
        Overall Acceptance Rate 54 of 142 submissions, 38%

        Contributors

        Other Metrics

        Bibliometrics & Citations

        Bibliometrics

        Article Metrics

        • 0
          Total Citations
        • 11
          Total Downloads
        • Downloads (Last 12 months)11
        • Downloads (Last 6 weeks)0
        Reflects downloads up to 20 Jan 2025

        Other Metrics

        Citations

        View Options

        Login options

        View options

        PDF

        View or Download as a PDF file.

        PDF

        eReader

        View online with eReader.

        eReader

        HTML Format

        View this article in HTML Format.

        HTML Format

        Media

        Figures

        Other

        Tables

        Share

        Share

        Share this Publication link

        Share on social media