Transforming Infrastructure Inspection by Integrating a UAS with a Continuum Robotic Arm and AI-enabled Multimodal Sensing for Comprehensive Damage Assessment

Uncrewed Aerial Systems (UAS) hold promise for revolutionizing the inspection of transportation infrastructure by enabling rapid and safe assessments. However, the application of UAS is predominantly limited to detecting surface-level defects, such as visible cracks, due to the reliance on vision sensors. This approach inherently misses subsurface damage, which, to date, requires direct contact-based methods (e.g., ultrasonic, magnetic, and radiographic techniques) that are currently carried out by manual inspection. This project aims to investigate a transformative approach to infrastructure inspection by developing (1) an integrated UAS platform equipped with a continuum robotic arm to enable contact-based inspection, (2) novel machine learning algorithms to fuse multimodal sensors (e.g., vision, ultrasonic) to predict damage modes more accurately. The continuum robotic arm will be based on lightweight and collapsible tensegrity structures, whereas the machine learning algorithms will be based on the recent transformer architecture. This proposed system aims to establish a foundational approach for future developments in multimodal and autonomous infrastructure inspection, significantly advancing the field by overcoming current limitations in damage assessment capabilities.

• Record URL:
  https://www.ctips.org/projects/details.php?id=623

Language

• English

Project

• Status: Active
• Funding: $60000
• Contract Numbers:

  69A3552348308

• Sponsor Organizations:

  Office of the Assistant Secretary for Research and Technology

  University Transportation Centers Program
  Department of Transportation
  Washington, DC  United States  20590
• Managing Organizations:

  Center for Transformative Infrastructure Preservation and Sustainability

  North Dakota State University
  Fargo, ND  United States  58108
• Project Managers:

  Tolliver, Denver

• Performing Organizations:

  Colorado State University

  Department of Civil and Environmental Engineering
  Campus Delivery 1372
  Fort Collins, CO  United States  80523
• Principal Investigators:

  Zhao, Jianguo

  Guo, Yanlin

  Mahmoud, Hussam

• Start Date: 20240716
• Expected Completion Date: 20260715
• Actual Completion Date: 0
• USDOT Program: University Transportation Centers Program
• Source Data: CTIPS-025

Subject/Index Terms

• TRT Terms: Artificial intelligence; Condition surveys; Drones; Inspection; Machine learning; Robots
• Subject Areas: Bridges and other structures; Data and Information Technology; Highways; Maintenance and Preservation;

Filing Info

• Accession Number: 01926482
• Record Type: Research project
• Source Agency: Center for Transformative Infrastructure Preservation and Sustainability
• Contract Numbers: 69A3552348308
• Files: UTC, RIP
• Created Date: Aug 5 2024 7:03PM