Intervention AUVs: The Next Challenge

While commercially available AUVs are routinely used in survey missions, a new set of applications exist which clearly demand intervention capabilities. The maintenance of: permanent underwater observatories, submerged oil wells, cabled sensor networks, pipes and the deployment and recovery of benthic stations are a few of them. These tasks are addressed nowadays using manned submersibles or work-class ROVs, equipped with teleoperated arms under human supervision. Although researchers have recently opened the door to future I-AUVs, a long path is still necessary to achieve autonomous underwater interventions. This paper reviews the evolution timeline in autonomous underwater intervention systems. Milestone projects in the state of the art are reviewed, highlighting their principal contributions to the field. To the best of the authors knowledge, only three vehicles have demonstrated some autonomous intervention capabilities so far: ALIVE, SAUVIM and GIRONA 500, being the last one the lightest one. In this paper GIRONA 500 I-AUV is presented and its software architecture discussed. Recent results in different scenarios are reported: 1) Valve turning and connector plugging/unplugging while docked to a subsea panel, 2) Free floating valve turning using learning by demonstration, and 3) Multipurpose free-floating object recovery. The paper ends discussing the lessons learned so far

OBJECT PERCEPTION IN UNDERWATER ENVIRONMENTS: A SURVEY ON SENSORS AND SENSING METHODOLOGIES

Underwater robots play a critical role in the marine industry. Object perception is the foundation for the automatic operations of submerged vehicles in dynamic aquatic environments. However, underwater perception encounters multiple environmental challenges, including rapid light attenuation, light refraction, or backscattering effect. These problems reduce the sensing devices’ signal-to-noise ratio (SNR), making underwater perception a complicated research topic. This paper describes the state-of-the-art sensing technologies and object perception techniques for underwater robots in different environmental conditions. Due to the current sensing modalities’ various constraints and characteristics, we divide the perception ranges into close-range, medium-range, and long-range. We survey and describe recent advances for each perception range and suggest some potential future research directions worthy of investigating in this field

Computer vision methods for underwater pipeline segmentation

Underwater pipeline inspection is usually conducted by Remotely Operated Vehicles (ROVs) equipped mainly with optical and acoustic sensors. During long inspections periods and low visibility conditions, traditional visual inspection becomes a tedious job and can lead to operator misinterpretations. Therefore, the automation of this process involves an improvement in the maintenance of the pipelines. This work presents an underwater pipeline segmentation system for rigid pipelines using a monocular camera. A color based edge detector was proposed, taking advantage of the pipeline geometry restrictions, besides tracking information. Segmented pipelines were transformed into a 2D top view representation. The system was evaluated with a dataset containing 7808 images, manually annotated, acquired during real inspection tasks. The system reached 96.5% of detection rate and 96.3% of segmentation accuracy.O processo de inspeção de tubulações submarinas é geralmente realizado por Veículos Operados Remotamente (ROVs) equipados principalmente com sensores óticos e acústicos. Durante longos períodos de inspeção e em condições de baixa visibilidade, o processo de inspeção visual torna-se cansativo e sujeito a falhas de interpretação por parte do operador. Portanto, a automação desse processo apresenta uma melhoria na manutenção das tubulações. Este trabalho apresenta um sistema de segmentação de tubulações rígidas submarinas usando uma câmera monocular. Um detector de bordas baseado na cor foi proposto aproveitando as restrições da geometria das tubulações e informações de rastreamento. Tubulações segmentadas foram transformadas em uma representação de vista superior 2D. O sistema foi avaliado com um conjunto de dados de 7808 imagens, anotados manualmente, obtidas em diferentes tarefas de inspeção reais. O sistema obteve 96.5% na taxa de detecção e 96,3% de acurácia na segmentação

Development Of A Vision System For Ship Hull Inspection

Penyelidikan ini memperkenalkan strategi pengawalan untuk memperbaiki prestasi pemeriksaan visual badan kapal dengan menggunakan kenderaan dalam air. This work introduces a strategy to improve the performance of visual ship hull inspection using a Remotely-Operated Vehicle (ROV) as its underwater vehicle platform

Development Of A Vision System For Ship Hull Inspection [K4165. Z94 2007 f rb].

Penyelidikan ini memperkenalkan strategi pengawalan untuk memperbaiki prestasi pemeriksaan visual badan kapal dengan menggunakan kenderaan dalam air. Kaedah yang dicadangkan bertujuan untuk membangunkan sebuah sistem yang secara visualnya sentiasa kekal selari pada permukaan badan kapal. This work introduces a strategy to improve the performance of visual ship hull inspection using a Remotely-Operated Vehicle (ROV) as its underwater vehicle platform. The proposed method is aimed at developing a system that will maintain the camera viewing angle parallel to the ship hull surface

3D reconstruction and motion estimation using forward looking sonar

Autonomous Underwater Vehicles (AUVs) are increasingly used in different domains including archaeology, oil and gas industry, coral reef monitoring, harbour’s security, and mine countermeasure missions. As electromagnetic signals do not penetrate underwater environment, GPS signals cannot be used for AUV navigation, and optical cameras have very short range underwater which limits their use in most underwater environments. Motion estimation for AUVs is a critical requirement for successful vehicle recovery and meaningful data collection. Classical inertial sensors, usually used for AUV motion estimation, suffer from large drift error. On the other hand, accurate inertial sensors are very expensive which limits their deployment to costly AUVs. Furthermore, acoustic positioning systems (APS) used for AUV navigation require costly installation and calibration. Moreover, they have poor performance in terms of the inferred resolution. Underwater 3D imaging is another challenge in AUV industry as 3D information is increasingly demanded to accomplish different AUV missions. Different systems have been proposed for underwater 3D imaging, such as planar-array sonar and T-configured 3D sonar. While the former features good resolution in general, it is very expensive and requires huge computational power, the later is cheaper implementation but requires long time for full 3D scan even in short ranges. In this thesis, we aim to tackle AUV motion estimation and underwater 3D imaging by proposing relatively affordable methodologies and study different parameters affecting their performance. We introduce a new motion estimation framework for AUVs which relies on the successive acoustic images to infer AUV ego-motion. Also, we propose an Acoustic Stereo Imaging (ASI) system for underwater 3D reconstruction based on forward looking sonars; the proposed system features cheaper implementation than planar array sonars and solves the delay problem in T configured 3D sonars