Center for Transformative Infrastructure Preservation and Sustainability

Project Details

Title:
Transforming Infrastructure Inspection by Integrating a UAS with a Continuum Robotic Arm for Potential Contact-Based Damage Assessment
Principal Investigators:
Jianguo Zhao, Yanlin Guo, and Hussam Mahmoud
University:
Status:
Active
Type:
Research
Year:
2024
Grant #:
69A3552348308 (IIJA)
Project #:
CTIPS-025
RiP #:
RH Display ID:
161254
Keywords:
artificial intelligence, condition surveys, drones, inspection, machine learning, robots
USDOT Strategic Goal:
Safety

Abstract

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 preliminarily investigate a transformative approach to infrastructure inspection by developing an integrated UAS platform equipped with a continuum robotic arm for contact-based inspection. The project will also conduct a preliminary evaluation of sensors suitable for contact-based infrastructure inspection, providing a basis for future sensor integration efforts. This proposed system aims to establish a foundational approach for future developments in multimodal and autonomous infrastructure inspection, advancing the field by overcoming current limitations in damage assessment capabilities.

Project Word Files

project files

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