SBIR Phase I: Georeferenced Augmented Reality for Knowledge-Based Excavator Control

该项目更广泛的影响/商业潜力源于其将挖掘机操作和控制从主要基于技能的活动转变为基于知识的实践的能力，从而显著提高了生产力和安全性。这反过来将有助于实现巨大的成本节约和减少对公众的潜在危害，提高美国建筑业的竞争力，并降低民用基础设施的生命周期成本。在制造业、运输业、采矿业和造船业等领域，从以技能为基础的流程向以知识为基础的流程过渡具有价值，这些领域也将产生这种好处。从长远来看，所提出的解决方案的意外公用事业罢工预警功能还可能为客户节省数百万美元的责任和机会成本，避免对生活和商业的破坏，并防止对工人和公众的人身危险。因此，该项目的社会效益和商业影响预计将是通过安全有效的挖掘，大大降低建筑和地下基础设施的成本。该小型企业创新研究（SBIR）第一阶段项目将把基于计算机视觉的基本运动跟踪技术转化为一种变革性的解决方案，用于在现场条件下跟踪挖掘机末端执行器（铲斗），并展示满足目标市场性能需求的能力。挖掘是一项典型的施工活动，每个操作员都面临两个主要问题：1）需要保持精确的坡度控制; 2）需要避免意外的公用设施罢工。该项目将克服这些痛点，并使用增强现实技术为操作员实时提供挖掘作业计划、目标坡度剖面和不断变化的坡度剖面的可视化，使操作员能够高精度地实现目标坡度，提高生产力和安全性。颠覆性创新是使用廉价的基于计算机视觉的跟踪：1）跟踪本地坐标系中挖掘机铲斗的位置; 2）跟踪同一坐标系中安装在机舱内的摄像机的位置，以在增强现实中可视化埋在地下的公用设施位置。广泛的现场测试已经证明，该技术相对于相机以小于一英寸的不确定性来跟踪标记，与当前的基于全球定位系统的方法相比提供了显著的优势，该方法对于所追求的应用是昂贵且不可靠的。

The broader impact/commercial potential of this project stems from its ability to transform excavator operation and control from a primarily skill-based activity to a knowledge-based practice, leading to significant increases in productivity and safety. This is turn will help realize enormous cost savings and reduction of potential hazards to the public, improve competitiveness of U.S. construction industry, and reduce life cycle costs of civil infrastructure. Such benefits will also accrue in fields such as manufacturing, transportation, mining, and ship-building where the transition from skill-based to knowledge-based processes is of value. In the long-run, the accidental utility strike warning capabilities of the proposed solution also have the potential to save millions of dollars in liability and opportunity costs for customers, and avoid disruptions to life and commerce, and prevent physical danger to workers and the public. The societal benefit and commercial impact of the project are thus expected to be the significant reductions in construction and underground infrastructure costs that will be possible through safe and efficient excavation. This Small Business Innovation Research (SBIR) Phase I project will translate fundamental computer-vision based motion-tracking technology into a transformative solution for tracking an excavator end-effector (bucket) in field conditions, and demonstrate the capability to meet target market performance demands. Excavation is a quintessential construction activity where every operator faces two major problems: 1) The need to maintain precise grade control; and 2) The need to avoid accidental utility strikes. This project will overcome these pain points and present operators with a visualization of excavation job plans, target grade profiles, and the evolving grade profile in real-time using augmented reality, allowing operators to achieve target grades with high precision, improved productivity, and safety. The disruptive innovation is the use of inexpensive computer-vision based tracking to: 1) track the position of an excavator bucket in a local coordinate system; and 2) track the position of a cabin-mounted camera in the same coordinate system to visualize buried utility locations in augmented reality. Extensive field testing has demonstrated that this technology tracks markers relative to a camera with an uncertainty of less than one inch, offering significant advantages over current global positioning system based methods that are expensive and unreliable for the pursued application.