Date of Graduation


Document Type


Degree Type



Statler College of Engineering and Mineral Resources


Lane Department of Computer Science and Electrical Engineering

Committee Chair

Powsiri Klinkhachorn.


The objective of this research is to develop an Unmanned Ground Vehicle (UGV) that can autonomously gather data for analysis of FRP bridge decks. Both ground penetrating radar (GPR) and infrared thermography (IRT) have shown promise in the field of non-destructive detection of defects in FRP decks. Even though both technologies can be effective, they each have certain limitations. For example, GPR is sensitive to water-filled defects while IRT is more sensitive to air-filled defects. This thesis investigates the effectiveness of combining and automating the data acquisition for each technique. Since both IRT and GPR analysis are subjective in nature, automating the data collection, including the heating preparation required with IRT analysis, involved with surveying an FRP deck may allow for a more objective analysis of the FRP deck. The reliability of the autonomous data acquisition of the UGV was assessed, as well as the effectiveness of combining IRT and GPR. Experimentation with various heat sources showed that passive heating should not be used for autonomous data acquisition. Testing showed that active heating with a strong heat source produced good quality IR images a reasonable amount of time. Analysis of these IR images with various image processing techniques, such as fuzzy c-means clustering, automatic defect detection schemes with approximately 87.5% detection rates could be implemented. An Unmanned Ground Vehicle (UGV) was created that combined an active heating system, an IR camera, and GPR analysis. A pipelining process was implemented that allows the UGV to perform the autonomous data acquisition as efficiently as possible. The UGV was then used to evaluate the effectiveness of combining IRT and GPR. Due to laboratory limitations, no actual testing was done that incorporates both analysis methods simultaneously. However, results show that the data collected can be used to determine both air and water filled defects and will provide valuable data when combined.