Delivering Maintenance and Repair Actions via Automated/Robotic Systems

Details

• Creators:
  Gong, Jie ; Liang, Xiao ; Bandelt, Matthew J
• Corporate Creators:
  Rutgers University. Center for Advanced Infrastructure and Transportation
• Corporate Contributors:
  United States. Department of Transportation. University Transportation Centers (UTC) Program ; United States. Department of Transportation. Office of the Assistant Secretary for Research and Technology
• Subject/TRT Terms:
  Artificial Intelligence Automation Infrastructure Maintenance Robotics
• Publication/ Report Number:
  CAIT-UTC-REG9
• Resource Type:
  Tech Report
• Geographical Coverage:
  United States
• Edition:
  Final Report 9/01/2018 – 12/31/2023
• Corporate Publisher:
  Center for Advanced Infrastructure and Transportation (CAIT) (UTC)
• Abstract:
  This study explores the emerging role of robotics in infrastructure inspection and repair. Through a multidisciplinary workshop and a series of proof-of-concept field studies, we evaluated the capabilities of advanced robotic platforms—particularly quadruped systems like Boston Dynamics' SPOT—and AI-powered remote sensing tools. Results showed strong potential for improving inspection accuracy, safety, and efficiency. Quadruped robots demonstrated excellent mobility in hazardous environments, while AI integration enhanced data analysis and defect detection. These findings highlight the promise of robotics in infrastructure management and the growing impact of AI in enabling autonomous, intelligent inspection systems.
• Format:
  PDF
• Funding:
  69A3551847102
• Collection(s):
  University Transportation Centers
• Main Document Checksum:
  urn:sha-512:7e642ddecb6f871adf4dce8dbfc484870518a3fbd27c3d882a74dc479d51794236a15a69c71bb4fd9c2e4747ded1031aed2a6afb9963e13893b93e214fe10db7
• Download URL:
  https://rosap.ntl.bts.gov/view/dot/82864/dot_82864_DS1.pdf
• File Type:
  [PDF - 987.68 KB ]