Infrastructure Inspection

Infrastructure inspection aims to automate the visual assessment of structures like bridges and power towers, improving efficiency and safety compared to traditional manual methods. Current research focuses on developing automated systems using computer vision techniques, including deep learning models like U-Net and the Segment Anything Model (SAM), to detect and classify damage such as cracks and spalling. These advancements leverage both image analysis and human-robot interaction systems, integrating expert knowledge to enhance accuracy and speed of inspection. The resulting improvements in efficiency and safety have significant implications for infrastructure maintenance and resource allocation.