3D Vision Systems for Industrial Bin-Picking Applications

被引:0
|
作者
Pochyly, Ales [1 ]
Kubela, Tomas [1 ]
Singule, Vladislav [1 ]
Cihak, Petr
机构
[1] Brno Univ Technol, Fac Mech Engn, Dept Robot & Robots, Brno 61669, Czech Republic
关键词
bin-picking; 3D vision; machine vision; robotics;
D O I
暂无
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
This paper relates to a vision-based system for robotic grasping of various objects randomly organized in a bin. In other words, this work deals with the bin-picking problem where the objects that are about to recognize by the vision system are placed in a bin non-oriented, interlocked, jumbled and/or heavily occluding each other. Concerning the industrial applications, demands for a functional technology to cope with the problem are still rising. In this paper we present a short review regarding the bin-picking applications followed by selected results concerned with the system structure description, control system structure, bin-picking methodology and pilot testing projects solutions.
引用
收藏
页码:63 / 68
页数:6
相关论文
共 50 条
  • [41] FPCC: Fast point cloud clustering-based instance segmentation for industrial bin-picking
    Xu, Yajun
    Arai, Shogo
    Liu, Diyi
    Lin, Fangzhou
    Kosuge, Kazuhiro
    NEUROCOMPUTING, 2022, 494 : 255 - 268
  • [42] C-LFNet: Central-Local Feature 3D point cloud instance segmentation Network for robot bin-picking
    Li, Pengchao
    Xu, Fang
    Wang, Jintao
    Guo, Haibing
    Miao, Li
    Su, Meng
    MEASUREMENT, 2024, 225
  • [43] Real-Time Industrial Bin-Picking with a Hybrid Deep Learning-Engineering Approach
    Lee, Sukhan
    Lee, Yeonho
    2020 IEEE INTERNATIONAL CONFERENCE ON BIG DATA AND SMART COMPUTING (BIGCOMP 2020), 2020, : 584 - 588
  • [44] Evaluation of Kinect Vision Sensor for Bin-Picking Applications Improved Component Separation Accuracy with Combined Use of Depth Map and Color Image
    Miyata, Shigeharu
    Yashiki, Yoshiyuki
    2014 13TH INTERNATIONAL CONFERENCE ON CONTROL AUTOMATION ROBOTICS & VISION (ICARCV), 2014, : 94 - 99
  • [45] Transfer Learning for Machine Learning-based Detection and Separation of Entanglements in Bin-Picking Applications
    Moosmann, Marius
    Spenrath, Felix
    Rosport, Johannes
    Melzer, Philipp
    Kraus, Werner
    Bormann, Richard
    Huber, Marco F.
    2022 IEEE/RSJ INTERNATIONAL CONFERENCE ON INTELLIGENT ROBOTS AND SYSTEMS (IROS), 2022, : 1123 - 1130
  • [47] Instance segmentation based 6D pose estimation of industrial objects using point clouds for robotic bin-picking
    Zhuang, Chungang
    Li, Shaofei
    Ding, Han
    ROBOTICS AND COMPUTER-INTEGRATED MANUFACTURING, 2023, 82
  • [48] Machine Learning Based Real-Time Industrial Bin-Picking: Hybrid and Deep Learning Approaches
    Lee, Sukhan
    Lee, Soojin
    PROCEEDINGS OF THE 2021 DESIGN, AUTOMATION & TEST IN EUROPE CONFERENCE & EXHIBITION (DATE 2021), 2021, : 597 - 602
  • [49] Domain Adaptation on Point Clouds for 6D Pose Estimation in Bin-picking Scenarios
    Zhao, Liang
    Sun, Meng
    Lv, Wei Jie
    Zhang, Xin Yu
    Zeng, Long
    2023 IEEE/RSJ INTERNATIONAL CONFERENCE ON INTELLIGENT ROBOTS AND SYSTEMS, IROS, 2023, : 2925 - 2931
  • [50] Efficient 3D Object Recognition for Unadjusted Bin Picking Automation
    Zheng, Yuchao
    Chen, Xiu
    Li, Yujie
    20TH INTERNATIONAL WIRELESS COMMUNICATIONS & MOBILE COMPUTING CONFERENCE, IWCMC 2024, 2024, : 262 - 268