Abstract

Underwater imaging is being increasingly helpful for the autonomous robots to reconstruct and map the marine environments which is fundamental for searching for pipelines or wreckages in depth waters. In this context, the accuracy of the information obtained from the environment is of extremely importance. This work presents a study about the accuracy of a reconfigurable stereo vision system while determining a dense disparity estimation for underwater imaging. The idea is to explore the advantage of this kind of system for underwater autonomous vehicles (AUV) since varying parameters like the baseline and the pose of the cameras make possible to extract accurate 3D information at different distances between the AUV and the scene. Therefore, the impact of these parameters is analyzed using a metric error of the point cloud acquired by a stereoscopic system. Furthermore, results obtained directly from an underwater environment proved that a reconfigurable stereo system can have some advantages for autonomous vehicles since, in some trials, the error was reduced by 0.05 m for distances between 1.125 and 2.675 m. Document type: Part of book or chapter of book

Abstract

Regular inspection of underwater communications (pipelines and cables) is actual problem of modern oil and gas industry. Specially equipped vessels, towed underwater devices and remote operated vehicles /ROV/ are applied for these purposes as usually, but quality of acquired data does not always allow revealing emergencies at the proper time. “Spot” inspections by ROVs give difficultly comparable data (Baker, 1991; Murray, 1991). The perspective solution of the problem is autonomous underwater vehicles /AUV/ application as “the intellectual carrier” of research equipment (Evans et al., 2003; Kojima et al., 1997). According (Ageev, 2005) the main goals of pipeline and cables inspection are: 1. more accurate position determination (searching and tracking); 2. pipe sagging and freespan detection and measurement; 3. terrain survey on each side of communication by means of high frequency side scan sonar /HF SSS/ and detection of extraneous objects; 4. detection of damages; 5. leakage detection of transported substances (for pipelines). The pipeline and cable inspection by means of AUV includes two stages: preliminary (communication search and detection) and the main (motion along the communication with carrying out of necessary measurements, i.e. tracking). Exact mutual orientation of AUV and inspected object is required in real time during the tracking stage. To solve inspection tasks AUV should be equipped with reliable detection systems for inspected object recognition. Video, electromagnetic and echo-sounder data can be used for these purposes. Each of these devices demonstrates optimal results for certain classes of objects in appropriate conditions. For example, metal pipelines have the significant sizes and can be detected by all listed above devices. While underwater cables have a small diameter, because of this applicability of acoustic methods is limited (Petillot et al., 2002). Process of communications search and detection is complicated, as a rule, with a poor visibility of the given objects (strewed with a ground, silted or covered by underwater flora and fauna). Experiments with the use of AUV for inspection of underwater communications have been carried out for a long time. Usually only one instrument, which AUV is equipped with, is used for object detection. O pe n A cc es s D at ab as e w w w .in te ch w eb .o rg Document type: Part of book or chapter of book

Abstract

To ensure their continuing integrity, the state of pipelines and cables needs to be monitored regularly. Divers, towfish ore remotely operated underwater vehicles (ROVs), which are traditionally used for cable & pipeline inspection, are time and human resources intensive. On the other hand, autonomous underwater vehicles (AUVs) represent a tool with great benefits. Therefore, a reliable localization and robust tracking system is required and it is the focus of this paper. The developed system will be tested for its performance in different pipeline layout scenarios.