Monitoring of data grabbing by multi-sensor parallel robot based on visual screening

被引:0
|
作者
Shang M. [1 ]
Zhang J. [1 ]
Han F. [1 ]
Yu M. [1 ]
机构
[1] Electric Power Research Institute of, Guangxi Power Grid Co., Ltd, Guangxi, Nanning
关键词
Grab; Monitoring; Multi-sensor; Parallel robot; Visual screening;
D O I
10.1504/IJMTM.2021.118803
中图分类号
学科分类号
摘要
In order to overcome the problems of low monitoring accuracy and efficiency in the existing monitoring methods of grab data, a new monitoring method of grab data of multi-sensor parallel robot based on visual screening is proposed. Multi-sensor data fusion is used to identify the robot’s pose. Based on visual screening technology, FH visual processing module is constructed by using FH visual controller, camera and LED light source, with the camera connection completed by using fz-vs camera line and FH visual controller. Transfer data information such as workpiece type coordinates to the NJ controller. The controller uses the network and servo driver to connect, and combines the robot pose detection results to realise the robot grasping data control. The experimental results show that this method has high monitoring accuracy and efficiency, and the shortest monitoring time is only 21 s. Copyright © 2021 Inderscience Enterprises Ltd.
引用
收藏
页码:200 / 217
页数:17
相关论文
共 50 条
  • [41] Factory Environmental Monitoring System based on Zigbee Technology and Multi-sensor Data Fusion
    Feng, Lu
    Lai, Wugang
    Yang, Chengyi
    Li, Jianan
    Yang, Biyun
    PROCEEDINGS OF 2023 THE 12TH INTERNATIONAL CONFERENCE ON NETWORKS, COMMUNICATION AND COMPUTING, ICNCC 2023, 2023, : 133 - 138
  • [42] Research on monitoring and environmental control of farmland operation based on multi-sensor data fusion
    Hua, Lei
    Gao, Jianen
    Zhou, Meifang
    Han, Saiqi
    Yin, Yan
    Bai, Shilun
    INTERNATIONAL JOURNAL OF ENVIRONMENTAL TECHNOLOGY AND MANAGEMENT, 2020, 23 (5-6) : 340 - 358
  • [43] Intelligent water quality monitoring system based on multi-sensor data fusion technology
    Liu Q.
    International Journal of Ambient Computing and Intelligence, 2021, 12 (04) : 43 - 63
  • [44] Autonomous localization technique of submarine in-pipe robot based on multi-sensor data fusion
    Research Institute of Robotics, Shanghai Jiaotong University, Shanghai 200240, China
    Shanghai Jiaotong Daxue Xuebao, 2008, 10 (1707-1711): : 1707 - 1711
  • [45] Multi-sensor and Multi-frequency Data Fusion for Structural Health Monitoring
    Ponsi, Federico
    Castagnetti, Cristina
    Bassoli, Elisa
    Mancini, Francesco
    Vincenzi, Loris
    PROCEEDINGS OF THE 10TH INTERNATIONAL OPERATIONAL MODAL ANALYSIS CONFERENCE, IOMAC 2024, VOL 2, 2024, 515 : 281 - 291
  • [46] Visual Marker based Multi-Sensor Fusion State Estimation
    Luis Sanchez-Lopez, Jose
    Arellano-Quintana, Victor
    Tognon, Marco
    Campoy, Pascual
    Franchi, Antonio
    IFAC PAPERSONLINE, 2017, 50 (01): : 16003 - 16008
  • [47] Detection for Joint Attention Based on A Multi-sensor Visual System
    Zhang, Wanqi
    Wang, Zhiyong
    Cai, Haibin
    Liu, Honghai
    PROCEEDINGS OF THE 2018 25TH INTERNATIONAL CONFERENCE ON MECHATRONICS AND MACHINE VISION IN PRACTICE (M2VIP), 2018, : 231 - 236
  • [48] Multi-sensor detection and control network technology based on parallel computing model in robot target detection and recognition
    Wei, Pengcheng
    Wang, Bo
    COMPUTER COMMUNICATIONS, 2020, 159 : 215 - 221
  • [49] Population estimation based on multi-sensor data fusion
    Lu, Zhenyu
    Im, Jungho
    Quackenbush, Lindi
    Halligan, Kerry
    INTERNATIONAL JOURNAL OF REMOTE SENSING, 2010, 31 (21) : 5587 - 5604
  • [50] A bionic manipulator based on multi-sensor data fusion
    Qian, Chenghui
    Li, Xiang
    Zhu, Jianfeng
    Liu, Tao
    Li, Ruilin
    Li, Bingyang
    Hu, Mengyuan
    Xin, Yi
    Xu, Yang
    INTEGRATED FERROELECTRICS, 2018, 192 (01) : 10 - 15