Autonomous Robotic Surface Inspection Using Computer Vision

  • Authors

    • Dr. Arvind Kumar Singh Professor, Jawaharlal Nehru University, India Author
    • Dr. Lakshmi Narayanan Associate Professor, Bharathidasan University, India Author

    DOI:

    https://doi.org/10.67228/30715725/IJIARE-2022PI4R1P

    Published 01-04-2022

  • Autonomous Robotics, Computer Vision, Surface Inspection, Deep Learning, Industrial Automation, Machine Vision, Defect Detection, Image Processing, Artificial Intelligence, Predictive Maintenance, Industry 4.0, Smart Manufacturing

    Issue

    Vol. 5 No. 1 (2022)

    Section

    Articles

    How to Cite

    [1]
    A. K. Singh and L. Narayanan, “Autonomous Robotic Surface Inspection Using Computer Vision”, IJIARE, vol. 5, no. 1, pp. 01–16, Jan. 2022, doi: 10.67228/30715725/IJIARE-2022PI4R1P.

  • Abstract

    Autonomous robotic surface inspection combines intelligent robotics with computer vision to enable accurate, real-time, and contactless detection of surface defects such as cracks, corrosion, scratches, dents, and coating degradation. Unlike manual inspection, it improves consistency, enhances safety, reduces inspection time, and lowers operational costs. By integrating AI, deep learning, edge computing, IIoT, and Digital Twin technologies, autonomous robots can navigate complex industrial environments, capture high-resolution images, and perform automated defect analysis with minimal human intervention. The proposed framework integrates robotic navigation, visual sensing, image processing, defect classification, and maintenance decision support to achieve reliable inspection across diverse industrial sectors. This approach supports predictive maintenance, improves quality assurance, and advances smart manufacturing in Industry 4.0.

  • References

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