YaBeSH Engineering and Technology Library

    • Journals
    • PaperQuest
    • YSE Standards
    • YaBeSH
    • Login
    View Item 
    •   YE&T Library
    • ASCE
    • Journal of Computing in Civil Engineering
    • View Item
    •   YE&T Library
    • ASCE
    • Journal of Computing in Civil Engineering
    • View Item
    • All Fields
    • Source Title
    • Year
    • Publisher
    • Title
    • Subject
    • Author
    • DOI
    • ISBN
    Advanced Search
    JavaScript is disabled for your browser. Some features of this site may not work without it.

    Archive

    Automated Part Placement for Precast Concrete Component Manufacturing: An Intelligent Robotic System Using Target Detection and Path Planning

    Source: Journal of Computing in Civil Engineering:;2025:;Volume ( 039 ):;issue: 001::page 04024044-1
    Author:
    Huanyu Wu
    ,
    Wei Zhang
    ,
    Weisheng Lu
    ,
    Junjie Chen
    ,
    Jianqiu Bao
    ,
    Yongqi Liu
    DOI: 10.1061/JCCEE5.CPENG-5948
    Publisher: American Society of Civil Engineers
    Abstract: Placing embedded parts (EPs), e.g., junction boxes or plastic cable ducts, in a precast concrete (PC) component is a fundamental and repetitive trade in its manufacturing. Yet, such trade is far from being automated to enhance PC component manufacturing productivity. This study presents an intelligent robotic system for automated part placement for PC component manufacturing by using target detection and path planning. The proposed system consists of an Aubo-i5 robotic arm, a Robotiq 2F-85 clamping claw, and an Intel Realsense D435i depth camera. An improved YOLOv5 target detection algorithm is proposed to automatically detect EPs with high precision, and a two-way two-threaded informed RRT* path planning algorithm is developed to optimize the robot movement. Using junction box placement as an experiment, performance of the system was evaluated by examining EP detection, clamping, path planning, and placement. The visual detection model achieved a mAP value of 99.5%. The efficiency of the path planning algorithm was improved by 37.7% compared with Bidirectional RRT* with close pathfinding quality. The final success rate of EP placement reached 99.8%. The research contributes to the field of PC component production by providing an automated system for EPs placement.
    • Download: (4.504Mb)
    • Show Full MetaData Hide Full MetaData
    • Get RIS
    • Item Order
    • Go To Publisher
    • Price: 5000 Rial
    • Statistics

      Automated Part Placement for Precast Concrete Component Manufacturing: An Intelligent Robotic System Using Target Detection and Path Planning

    URI
    http://yetl.yabesh.ir/yetl1/handle/yetl/4304145
    Collections
    • Journal of Computing in Civil Engineering

    Show full item record

    contributor authorHuanyu Wu
    contributor authorWei Zhang
    contributor authorWeisheng Lu
    contributor authorJunjie Chen
    contributor authorJianqiu Bao
    contributor authorYongqi Liu
    date accessioned2025-04-20T10:10:38Z
    date available2025-04-20T10:10:38Z
    date copyright9/24/2024 12:00:00 AM
    date issued2025
    identifier otherJCCEE5.CPENG-5948.pdf
    identifier urihttp://yetl.yabesh.ir/yetl1/handle/yetl/4304145
    description abstractPlacing embedded parts (EPs), e.g., junction boxes or plastic cable ducts, in a precast concrete (PC) component is a fundamental and repetitive trade in its manufacturing. Yet, such trade is far from being automated to enhance PC component manufacturing productivity. This study presents an intelligent robotic system for automated part placement for PC component manufacturing by using target detection and path planning. The proposed system consists of an Aubo-i5 robotic arm, a Robotiq 2F-85 clamping claw, and an Intel Realsense D435i depth camera. An improved YOLOv5 target detection algorithm is proposed to automatically detect EPs with high precision, and a two-way two-threaded informed RRT* path planning algorithm is developed to optimize the robot movement. Using junction box placement as an experiment, performance of the system was evaluated by examining EP detection, clamping, path planning, and placement. The visual detection model achieved a mAP value of 99.5%. The efficiency of the path planning algorithm was improved by 37.7% compared with Bidirectional RRT* with close pathfinding quality. The final success rate of EP placement reached 99.8%. The research contributes to the field of PC component production by providing an automated system for EPs placement.
    publisherAmerican Society of Civil Engineers
    titleAutomated Part Placement for Precast Concrete Component Manufacturing: An Intelligent Robotic System Using Target Detection and Path Planning
    typeJournal Article
    journal volume39
    journal issue1
    journal titleJournal of Computing in Civil Engineering
    identifier doi10.1061/JCCEE5.CPENG-5948
    journal fristpage04024044-1
    journal lastpage04024044-14
    page14
    treeJournal of Computing in Civil Engineering:;2025:;Volume ( 039 ):;issue: 001
    contenttypeFulltext
    DSpace software copyright © 2002-2015  DuraSpace
    نرم افزار کتابخانه دیجیتال "دی اسپیس" فارسی شده توسط یابش برای کتابخانه های ایرانی | تماس با یابش
    yabeshDSpacePersian
     
    DSpace software copyright © 2002-2015  DuraSpace
    نرم افزار کتابخانه دیجیتال "دی اسپیس" فارسی شده توسط یابش برای کتابخانه های ایرانی | تماس با یابش
    yabeshDSpacePersian