Design of Autonomous Inspection Robots for Infrastructure Monitoring

  • Authors

    • Dr. Pooja Agarwal Professor, Aligarh Muslim University, India. Author
    • Dr. Rakesh Chandra Associate Professor, University of Calcutta, India. Author

    DOI:

    https://doi.org/10.67228/30715725/IJIARE-2020PII4H7C

    Published 07-02-2020

  • Autonomous Inspection Robot, Infrastructure Monitoring, Mobile Robots, Computer Vision, Structural Health Monitoring, Sensor Fusion, Defect Detection, Wireless Communication, Robotics, Intelligent Monitoring Systems

    Issue

    Vol. 3 No. 2 (2020)

    Section

    Articles

    How to Cite

    [1]
    P. Agarwal and R. Chandra, “Design of Autonomous Inspection Robots for Infrastructure Monitoring”, IJIARE, vol. 3, no. 2, pp. 01–18, Jul. 2020, doi: 10.67228/30715725/IJIARE-2020PII4H7C.

  • Abstract

    Rapid urbanization, industrialization, and aging infrastructure have increased the need for efficient monitoring systems. Traditional manual inspections of bridges, tunnels, pipelines, dams, railway tracks, and industrial facilities are costly, time-consuming, labor-intensive, and risky. Autonomous inspection robots offer an advanced solution for smart infrastructure monitoring and maintenance. This study reviews autonomous inspection robots developed before February 2019, focusing on their design, navigation, sensors, communication systems, and control methods. These robots use technologies such as LiDAR, ultrasonic sensors, infrared cameras, thermal imaging, GPS, and wireless communication for real-time monitoring, defect detection, and predictive maintenance. Machine learning and computer vision further improve inspection accuracy. Different robot types, including wheeled, tracked, aerial, climbing, underwater, and hybrid robots, are compared based on mobility, adaptability, energy efficiency, and inspection performance. The paper also proposes an autonomous wheeled inspection robot using sensor fusion and computer vision for obstacle avoidance, wireless communication, and autonomous navigation. Results show that autonomous inspection robots improve safety, fault detection, and inspection efficiency compared to manual methods. Challenges such as power consumption, communication delays, localization errors, and sensor calibration are discussed. Future developments involving AI, IoT, cloud robotics, edge computing, swarm robotics, and digital twins are expected to enhance intelligent infrastructure monitoring systems.

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