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Intelligent road surface autonomous inspection.

Authors :
Tovanche-Picon, Hector
Garcia-Tena, Lorenzo
Garcia-Teran, Miguel A.
Flores-Abad, Angel
Source :
Evolutionary Intelligence; Jun2024, Vol. 17 Issue 3, p1481-1489, 9p
Publication Year :
2024

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%. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
18645909
Volume :
17
Issue :
3
Database :
Complementary Index
Journal :
Evolutionary Intelligence
Publication Type :
Academic Journal
Accession number :
178444534
Full Text :
https://doi.org/10.1007/s12065-023-00841-3