Pipe inspection is a critical process in many industries, including oil and gas. Conventional practice relies on a range of Non-Destructive Testing (NDT) approaches such as ultrasonic and magnetic flux leakage methods. While these approaches can provide high accuracy wall thickness measurements, which can be used to monitor corrosion, they provide poor visualizations, and are typically unable to provide full pipe coverage. Moreover, they cannot be used to localize where in the pipe a defect is without expensive and possibly restricted sensors such as Inertial Navigation Systems. We have developed an automated vision-based approach that builds high-resolution 3D appearance maps of pipes and provides vehicle localization. These maps include both structure and appearance information, and can be used for direct metric measurement of pipe wall thickness, or as input to automatic corrosion detection algorithms. They may also be imported into 3D rendering engines to provide effective visualization of a pipe network. Our most recent system uses a wide angle of view fisheye camera which enables full pipe coverage and is sufficiently compact for practical applications. Our approach to mapping and localization builds from state-of-the-art visual odometry methods and extends them to deal with (visually) feature poor engineered environments. We present the results of this work using image datasets collected within our constructed pipe network. A range of empirical results are presented to validate the approach.


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