Research on computer vision enhancement in intelligent robot based on machine learning and deep learning

被引:0
|
作者
Yuhan Ding
Lisha Hua
Shunlei Li
机构
[1] Facoltà Di Ingegneria Dell’Università Di Bologna,Mechanical Engineering
[2] City University of Hongkong,State Key Laboratory of Tribology
[3] Tsinghua University,undefined
来源
关键词
Machine learning; Deep learning; Robotics; Machine vision;
D O I
暂无
中图分类号
学科分类号
摘要
The stable operation of intelligent robots requires the effective support of machine vision technology. In order to improve the effect of robot machine vision recognition, based on deep learning, this paper, under the guidance of machine learning ideas, proposes a target detection framework that combines target recognition and target tracking based on the efficiency advantages of the KCF visual tracking algorithm. Moreover, this paper designs a vision system based on a high-resolution color camera and TOF depth camera. In addition, by modeling the coordinate conversion relationship of the same object in the camera coordinate system of two cameras, the projection relationship of the depth map collected by the TOF camera to the pixel coordinate system of the high-resolution color camera is determined. In addition, this paper designs experiments to verify the performance of the model. The research results show that the method proposed in this paper has a certain effect.
引用
收藏
页码:2623 / 2635
页数:12
相关论文
共 50 条
  • [21] Intelligent welding robot system based on deep learning
    Ma, Xufeng
    Pan, Shuwen
    Li, Yanjun
    Feng, Chao
    Wang, Aoran
    2019 CHINESE AUTOMATION CONGRESS (CAC2019), 2019, : 2944 - 2949
  • [22] Deep Learning-Based Intelligent Robot in Sentencing
    Chen, Xuan
    FRONTIERS IN PSYCHOLOGY, 2022, 13
  • [23] Research progress of computer vision tasks based on deep learning and SAE network
    Ling, Shijia
    Yi, Qiaoling
    Lan, Banru
    Liu, Liangfang
    APPLIED MATHEMATICS AND NONLINEAR SCIENCES, 2023, 8 (02) : 985 - 994
  • [24] Robot for Ball Fetch-and-Carry with Computer Vision in Deep Learning
    Su, Limin
    Huang, Chao-Jen
    Liu, Mei
    Lu, Bing-Yuh
    Che, Jidong
    Wang, Ximiao
    Feng, Jiqi
    Li, Changyong
    Feng, Youhong
    Mo, Yueliu
    2021 23RD INTERNATIONAL CONFERENCE ON ADVANCED COMMUNICATION TECHNOLOGY (ICACT 2021): ON-LINE SECURITY IN PANDEMIC ERA, 2021, : 435 - 438
  • [25] Robot for Ball Fetch-and-Carry with Computer Vision in Deep Learning
    Su, Limin
    Huang, Chao-Jen
    Liu, Mei
    Lu, Bing-Yuh
    Che, Jidong
    Wang, Ximiao
    Feng, Jiqi
    Li, Changyong
    Feng, Youhong
    Mo, Yueliu
    2022 24TH INTERNATIONAL CONFERENCE ON ADVANCED COMMUNICATION TECHNOLOGY (ICACT): ARITIFLCIAL INTELLIGENCE TECHNOLOGIES TOWARD CYBERSECURITY, 2022,
  • [26] Research on Maize Seed Classification and Recognition Based on Machine Vision and Deep Learning
    Xu, Peng
    Tan, Qian
    Zhang, Yunpeng
    Zha, Xiantao
    Yang, Songmei
    Yang, Ranbing
    AGRICULTURE-BASEL, 2022, 12 (02):
  • [28] Research on an intelligent pineapple pre-harvest anti-lodging method based on deep learning and machine vision
    Liu, Tian -Hu
    Qiu, Jian
    Liu, Ying
    Li, Jia-Yi
    Chen, Si -Yuan
    Lai, Jia-Shang
    Mai, Bao-Feng
    COMPUTERS AND ELECTRONICS IN AGRICULTURE, 2024, 218
  • [29] The Navigation of Home Service Robot Based on Deep Learning and Machine Learning
    Yan, Yupei
    Ma, Weimin
    Wong, Sengfat
    Yin, Xuemei
    Pan, Qiang
    Liao, Zhiwen
    Lin, Xiaoxin
    JOURNAL OF ROBOTICS, 2024, 2024
  • [30] Computer Vision and Machine Learning Based Grape Fruit Cluster Detection and Yield Estimation Robot
    Chauhan, Amit
    Singh, Mandeep
    JOURNAL OF SCIENTIFIC & INDUSTRIAL RESEARCH, 2022, 81 (08): : 866 - 872