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
  • [1] Research on computer vision enhancement in intelligent robot based on machine learning and deep learning
    Ding, Yuhan
    Hua, Lisha
    Li, Shunlei
    NEURAL COMPUTING & APPLICATIONS, 2022, 34 (04): : 2623 - 2635
  • [2] RESEARCH ON VISION SYSTEM OF INTELLIGENT SORTING ROBOT BASED ON DEEP LEARNING
    Li, Z. X.
    Zhang, Q.
    Huang, B. W.
    Miao, Y. X.
    METALURGIJA, 2025, 64 (1-2): : 69 - 71
  • [3] Robot Indoor Navigation Based on Computer Vision and Machine Learning
    Mo, Hongwei
    Luo, Chaomin
    Liu, Kui
    ADVANCES IN SWARM INTELLIGENCE, ICSI 2016, PT II, 2016, 9713 : 528 - 534
  • [4] Firefighting robot with deep learning and machine vision
    Amit Dhiman
    Neel Shah
    Pranali Adhikari
    Sayali Kumbhar
    Inderjit Singh Dhanjal
    Ninad Mehendale
    Neural Computing and Applications, 2022, 34 : 2831 - 2839
  • [5] Firefighting robot with deep learning and machine vision
    Dhiman, Amit
    Shah, Neel
    Adhikari, Pranali
    Kumbhar, Sayali
    Dhanjal, Inderjit Singh
    Mehendale, Ninad
    NEURAL COMPUTING & APPLICATIONS, 2022, 34 (04): : 2831 - 2839
  • [6] Computer Vision and Machine Learning for Intelligent Sensing Systems
    Tian, Jing
    SENSORS, 2023, 23 (09)
  • [7] The obstacles detection for outdoor robot based on computer vision in deep learning
    Chen, Hsuan
    Chiu, Wen-Hsin
    Yu, Jian-Cheng
    Chen, Hsiang-Chieh
    Wang, Wen-June
    2019 IEEE 9TH INTERNATIONAL CONFERENCE ON CONSUMER ELECTRONICS (ICCE-BERLIN), 2019, : 184 - 188
  • [8] Research on Computer Vision Technology based on Deep Learning Algorithm
    Jin, Jian
    Zhang, Xinmiao
    Dai, Yuquan
    BASIC & CLINICAL PHARMACOLOGY & TOXICOLOGY, 2020, 127 : 18 - 18
  • [9] Research on intelligent damage detection of far-sea cage based on machine vision and deep learning
    Liao, Wenxuan
    Zhang, Shubin
    Wu, Yinghao
    An, Dong
    Wei, Yaoguang
    AQUACULTURAL ENGINEERING, 2022, 96
  • [10] Research on Robot Intelligent Control Method Based on Deep Reinforcement Learning
    Rao, Shu
    2022 6TH INTERNATIONAL SYMPOSIUM ON COMPUTER SCIENCE AND INTELLIGENT CONTROL, ISCSIC, 2022, : 221 - 225