TARGETLESS PHOTOGRAMMETRY NETWORK SIMULATION FOR INSPECTION PLANNING IN OIL AND GAS INDUSTRY
Keywords: Pipeline inspection, Flexible riser, Photogrammetry, ROS/Gazebo, RPAS, UAV, Oil and gas
Abstract. The oil and gas offshore industry demands regular inspections of components and structures that are subjected to extreme operational and environmental conditions. In this context, risers are pipelines that transport mainly oil, gas, water, and cables between submarine structures and the surface offshore platform, in the portion not touching the ocean floor. The emerged part of these risers is typically inspected by industrial climbing, which is a very time-consuming activity, has high operational costs, is dangerous and has a strong dependence on inspector skills. Remotely Piloted Aircraft Systems (RPAS) have been recently used for visual inspection of risers, however, no quantitative or geometrical evaluation has been conducted using this kind of image acquisition yet. An image-based measurement technique, such as close-range photogrammetry, can provide a 3D reconstruction using images, but a series of requisites is mandatory to achieve good results as image acquisition sequence, overlap, camera positioning network, spatial resolution and object texture in non-prepared and targetless scenes. The analysis of different image acquisition strategies using a real RPAS is too difficult because it demands a lot of time, good weather, daylight, and a scene similar to where risers are installed. An alternative is to use simulation. In this paper a ROS/Gazebo simulation is described and used to create a realistic textured 3D virtual environment of the platform, risers and RPA, providing a fast and low-cost solution to simulate different RPA trajectories for photogrammetry image acquisition in targetless scenes. These trajectories are evaluated by comparing the measured risers through photogrammetry to its CAD/simulated model. Since the scene is not prepared, the RPA position/orientation or a stereo vision setup can be used to set scale to the measurement result. The best trajectory found during simulations was also evaluated in a real experiment.