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Intelligent road surface autonomous inspection

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Abstract

With the advancement of artificial intelligence, autonomous machines are featured with the ability to diagnose and assess the structural health of different systems. This paper presents a scalable mobile platform employed to autonomously and intelligently detect online small cracks on roads using a live camera feed and Artificial Intelligence (AI) methods. The robotic artifact is equipped with a vision-based localization system to enable autonomous navigation areas where GPS (Global Positioning System) may be poor or intermittent. The proposed approach runs at the edge a model of Convolutional Neuronal Networks (CNN) based on the Resnet 18 architecture to classify the image feed between cracks and those without cracks after training them with a combination of two public data sets and a data set generated in-house. The mobile robotic platform is scalable, depending on the particular context and requirements of the application. As opposed to off-line assessment tools, experimental results show the real-time capabilities of the system to autonomously navigate and detect cracks on a pavement structure with an accuracy of 95%.

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Funding

The authors declare that no funds, grants, or other support were received during the preparation of this manuscript

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Authors and Affiliations

  1. Department of Industrial and Manufacturing Engineering, The Autonomous University of Ciudad Juarez, 32584, Ciudad Juarez, Chihuahua, Mexico

    Hector Tovanche-Picon, Lorenzo Garcia-Tena & Miguel A. Garcia-Teran

  2. Aerospace and Mechanical Engineering Department, The University of Texas at El Paso, El Paso, TX, 79968, USA

    Angel Flores-Abad

Authors
  1. Hector Tovanche-Picon
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  2. Lorenzo Garcia-Tena
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  3. Miguel A. Garcia-Teran
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  4. Angel Flores-Abad
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Contributions

All authors contributed to the study conception and design. Material preparation, data collection and analysis were performed by HT-P, LG-T, MAG-T and AF-A. The first draft of the manuscript was written by HT-P and all authors commented on previous versions of the manuscript. All authors read and approved the final manuscript.

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Correspondence to Angel Flores-Abad.

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Tovanche-Picon, H., Garcia-Tena, L., Garcia-Teran, M.A. et al. Intelligent road surface autonomous inspection. Evol. Intel. 17, 1481–1489 (2024). https://doi.org/10.1007/s12065-023-00841-3

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  • DOI: https://doi.org/10.1007/s12065-023-00841-3

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