The development of bridge inspection solutions has been discussed in the recent past. In this dissertation, significant development and improvement on the state-of-the-art in the field of bridge inspection using multiple sensors (e.g. ground penetrating radar (GPR) and visual sensor) has been proposed. In the first part of this research (discussed in chapter 3), the focus is towards developing effective and novel methods for rebar detection and localization for sub-surface bridge inspection of steel rebars. The data has been collected using Ground Penetrating Radar (GPR) sensor on real bridge decks. In this regard, a number of different approaches have been successively developed that continue to improve the state-of-the-art in this particular research area. The second part (discussed in chapter 4) of this research deals with the development of an automated system for steel bridge defect detection system using a Multi-Directional Bicycle Robot. The training data has been acquired from actual bridges in Vietnam and validation is performed on data collected using Bicycle Robot from actual bridge located in Highway-80, Lovelock, Nevada, USA. A number of different proposed methods have been discussed in chapter 4. The final chapter of the dissertation will conclude the findings from the different parts and discuss ways of improving on the existing works in the near future
