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A Framework for Using UAVs to Detect Pavement Damage Based on Optimal Path Planning and Image Splicing

Author

Listed:
  • Runmin Zhao

    (School of Transportation, Southeast University, Nanjing 211189, China)

  • Yi Huang

    (School of Transportation, Southeast University, Nanjing 211189, China)

  • Haoyuan Luo

    (School of Transportation, Southeast University, Nanjing 211189, China)

  • Xiaoming Huang

    (School of Transportation, Southeast University, Nanjing 211189, China
    National Demonstration Center for Experimental Education of Road and Traffic Engineering, Southeast University, Nanjing 211189, China)

  • Yangzezhi Zheng

    (School of Transportation, Southeast University, Nanjing 211189, China)

Abstract

In order to investigate the use of unmanned aerial vehicles (UAVs) for future application in road damage detection and to provide a theoretical and technical basis for UAV road damage detection, this paper determined the recommended flight and camera parameters based on the needs of continuous road image capture and pavement disease recognition. Furthermore, to realize automatic route planning and control, continuous photography control, and image stitching and smoothing tasks, a UAV control framework for road damage detection, based on the Dijkstra algorithm, the speeded-up robust features (SURF) algorithm, the random sampling consistency (RANSAC) algorithm, and the gradual in and out weight fusion method, was also proposed in this paper. With the Canny operator, it was verified that the road stitched long image obtained by the UAV control method proposed in this paper is applicable to machine learning pavement disease identification.

Suggested Citation

  • Runmin Zhao & Yi Huang & Haoyuan Luo & Xiaoming Huang & Yangzezhi Zheng, 2023. "A Framework for Using UAVs to Detect Pavement Damage Based on Optimal Path Planning and Image Splicing," Sustainability, MDPI, vol. 15(3), pages 1-26, January.
    • Handle: RePEc:gam:jsusta:v:15:y:2023:i:3:p:2182-:d:1045591
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    Cited by:

    1. Serhii Semenov & Magdalena Krupska-Klimczak & Patryk Mazurek & Minjian Zhang & Olena Chernikh, 2025. "Improving Unmanned Aerial Vehicle Security as a Factor in Sustainable Development of Smart City Infrastructure: Automatic Dependent Surveillance–Broadcast (ADS-B) Data Protection," Sustainability, MDPI, vol. 17(4), pages 1-29, February.

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