Advancing Underwater Vision for 3D (AUV3D)

海底资产的安全高效建设、运营和退役对英国和全球能源生产至关重要。对于海上可再生能源来说，这一点尤其如此，因为成本效率对于提供清洁电力是必要的，这种清洁电力与其他低碳系统相比具有成本竞争力，并且规模可负担得起。从建造到退役，水下测量提供数据来监测状况，预测资产寿命并确保环境得到保护。我们的目标是通过从小型远程操作水下航行器提供实时、密集的3D点云数据，实现效率和安全性的飞跃。这将使更小的船只能够使用更少的船员，没有潜水员，并消除了将人们置于危险之中的需要。与传统的视觉测量相比，3D数据可以实现精确的测量和可重复、可靠的资产状况监测指标。最终，实时3D可以为全自动水下航行器提供精确的导航，从而减少人力并进一步提高效率。高质量的3D视觉数据也是将人工智能和深度学习解决方案应用于3D图像的先决条件，从而实现更大的自主性和可靠的可重复测量。AUV 3D项目的主要目标是原型设计和演示高质量水下智能立体相机系统的可行性。该系统将实现水下3D的创新，实时处理从水下视频调查。为此，我们将利用摄像头技术和嵌入式GPU计算的最新进展，这些技术使人工智能能够用于准确评估水下3D场景。通过展示在具有挑战性和极端的海底环境中从相机产生实时3D数据所需的软件和硬件的可行性，我们能够开发基于完整视觉的水下机器人人工智能。智能（RAI）调查解决方案。这有可能创造出小型、功能强大、智能的自动驾驶汽车，并允许更有效的调查，减少受伤害的人。

Safe and efficient construction, operation and decommissioning of subsea assets is critically important to UK and worldwide energy production. This is particularly true for offshore renewable energy where cost efficiencies are necessary to deliver clean power power that is cost competitive with other low carbon systems and at an affordable scale. From construction to decommissioning, underwater survey provides the data to monitor condition, predict asset life and ensure the environment is protected. We aim to deliver a step change in efficiency and safety by delivering live, dense, 3D point cloud data from small, Remotely Operated Underwater Vehicles. This will enable smaller vessels to be used with fewer crew, no divers, and removing the need to put people at risk. Compared to traditional visual survey, 3D data allows accurate measurement and repeatable, reliable metrics for asset condition monitoring. Ultimately, live 3D enables accurate navigation for fully autonomous underwater vehicles reducing manpower and increasing efficiency yet further. Quality 3D visual data is also a prerequisite to applying artificial intelligence and deep learning solutions to 3D images thereby enabling greater autonomy and reliably repeatable measurements.The key objective of the AUV3D project is to prototype and demonstrate the feasibility of a high-quality underwater, intelligent, stereo camera system. This system will enable innovative, real-time processing of underwater 3D from ROV video survey. To do this we will exploit recent advances in both camera technology and embedded GPU computing, and together these technologies enable Artificial Intelligence to be used to accurately to assess underwater 3D scenes.By demonstrating the feasibility of the software and hardware necessary to produce live 3D data from cameras in the challenging and extreme subsea environment we enable the development of a complete vision based underwater Robotic Artificial Intelligence (RAI) survey solution. This has the potential to create small, capable, intelligent autonomous vehicles and allow more efficient survey with fewer people in harm's way.