Visual feedback–based heading control of autonomous underwater vehicle for pipeline corrosion inspection

Underwater robotics and imaging have emerged as an attractive field due to complications for human divers in a deepwater environment. Inspection of various installations in an underwater environment is carried out by underwater vehicles. The equipment that is used at present requires high computational cost and dedicated only to single task. This results in an expensive hardware and application-oriented technology, hence restricting the versatility of the underwater vehicle. This article proposes a visual feedback–based heading control and tracking method for the autonomous underwater vehicle to provide a versatile solution. The proposed method is used for subsea pipeline corrosion inspection subjected to hydrodynamic disturbances. There are two parts of this study: the first part includes the heading control of the underwater vehicle using visual feedback to follow the pipeline, whereas the second part involves underwater image enhancement and dehazing using wavelet-based fusion for corrosion estimation. The visual feedback and corrosion estimation rely on the same image data during the inspection of the pipeline, hence, reducing the complexity of the overall algorithm. The performance of the proposed method is evaluated on image dataset acquired in an underwater environment where the camera is mounted on the underwater vehicle.