Gas Pipeline Inspection Using Autonomous Robots With Omni-Directional Cameras

Abstract

Maintenance of pipelines is a major concern for oil and gas companies and millions of dollars are spent on preventive inspections every year. The type of equipment used in carrying out inspections is expensive and very sophisticated requiring very specialized manpower. Here, a novel approach to pipeline inspection is presented using a small mobile robot and a catadioptric omni-directional vision system. The system captures panoramic videos using conical and/or hyperbolic mirrors, which are transmitted to a monitoring station to examine the inner surface of gas pipelines. The videos are prepped, unwrapped, and un-warped to obtain a realistic flat image of the whole inner surface of the pipeline. The Simulated Annealing optimization method is implemented to optimize the system parameters using different mirror shapes and unwrapping and un-warping techniques. Simulations and experimental studies using a mobile robot equipped with a CCD camera and a conical mirror are presented here to demonstrate the viability of this inspection technique. The developed robotic system can be used to visually pre-scan pipelines before using much more expensive tools such as magnetic flux leakage (MFL) or ultrasound (UT) based inspection systems. These latter tools cost tens of thousands of dollars per hour and will be used only after suspicious areas are visually detected. This will reduce the inspection time and cost significantly.