Automated Robotic Monitoring and Inspection of Steel Structures and Bridges
This addresses the need for efficient and automated inspection of steel infrastructure, though it appears incremental as it applies existing computer vision methods to a new robotic platform.
The paper tackles the problem of monitoring steel structures and bridges by developing a climbing robot that collects visual and 3D data in real-time, with results showing successful data collection and automated crack detection on test images.
This paper presents visual and 3D structure inspection for steel structures and bridges using a developed climbing robot. The robot can move freely on a steel surface, carry sensors, collect data and then send to the ground station in real time for monitoring as well as further processing. Steel surface image stitching and 3D map building are conducted to provide a current condition of the structure. Also, a computer vision-based method is implemented to detect surface defects on stitched images. The effectiveness of the climbing robot's inspection is tested in multiple circumstances to ensure strong steel adhesion and successful data collection. The detection method was also successfully evaluated on various test images, where steel cracks could be automatically identified, without the requirement of some heuristic reasoning.