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首页> 外文期刊>International Journal of Advanced Robotic Systems >Visual feedback-based heading control of autonomous underwater vehicle for pipeline corrosion inspection
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Visual feedback-based heading control of autonomous underwater vehicle for pipeline corrosion inspection

机译:基于视觉反馈的管道腐蚀检查自主水下车辆标题控制

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摘要

Underwater robotics and imaging have emerged as an attractive field due to complications for human divers in a deepwater environment. Inspection of various installations in an underwater environment is carried out by underwater vehicles. The equipment that is used at present requires high computational cost and dedicated only to single task. This results in an expensive hardware and application-oriented technology, hence restricting the versatility of the underwater vehicle. This article proposes a visual feedback-based heading control and tracking method for the autonomous underwater vehicle to provide a versatile solution. The proposed method is used for subsea pipeline corrosion inspection subjected to hydrodynamic disturbances. There are two parts of this study: the first part includes the heading control of the underwater vehicle using visual feedback to follow the pipeline, whereas the second part involves underwater image enhancement and dehazing using wavelet-based fusion for corrosion estimation. The visual feedback and corrosion estimation rely on the same image data during the inspection of the pipeline, hence, reducing the complexity of the overall algorithm. The performance of the proposed method is evaluated on image dataset acquired in an underwater environment where the camera is mounted on the underwater vehicle.
机译:由于深水环境中的人类潜水员并发症,水下机器人和成像被出现为有吸引力的领域。通过水下车辆进行水下环境中的各种装置的检查。目前使用的设备需要高计算成本并仅限于单一任务。这导致昂贵的硬件和面向应用的技术,因此限制了水下车辆的多功能性。本文提出了一种基于视觉反馈的标题控制和跟踪方法,用于自主水下车辆提供多功能解决方案。该方法用于对流体动力干扰进行的海底管道腐蚀检查。本研究中有两部分:第一部分包括使用视觉反馈的水下车辆的前线控制,以跟随管道,而第二部分涉及使用基于小波的熔化进行腐蚀估算的水下图像增强和去除湿。视觉反馈和腐蚀估计在检查管道期间依赖于相同的图像数据,因此降低了整个算法的复杂性。所提出的方法的性能在在水下环境中获取的图像数据集进行评估,其中相机安装在水下车辆上。

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