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

SBIR 第一阶段：基于知识的挖掘机控制的地理参考增强现实

• 批准号: 1448453
• 负责人: Suyang Dong
• 金额: $ 15万
• 依托单位: PERCEPTION ANALYTICS & ROBOTICS LLC
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2015
• 资助国家: 美国
• 起止时间: 2015-01-01 至 2016-06-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1448453&HistoricalAwards=false
• 关键词: SBIR; Phase; Georeferenced; Augmented; Reality

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.

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率和安全性。这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、运输、采矿和造船等领域，从以技能为基础的流程向以知识为基础的流程过渡是有价值的，这些领域也将产生这种好处。从长远来看，拟议解决方案的意外公用事业罢工预警功能还有可能为客户节省数百万美元的责任和机会成本，避免对生活和商业造成干扰，并防止对工人和公众造成人身危险。因此，该项目的社会效益和商业影响预计将是通过安全和有效的挖掘可能大幅减少建筑和地下基础设施费用。这个小型企业创新研究(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在现场条件下跟踪挖掘机末端执行器(铲斗)的变革性解决方案，并展示满足目标市场性能需求的能力。挖掘是一项典型的建筑活动，每个操作员都面临着两个主要问题：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，并利用增强现实技术为运营商提供实时的挖掘作业计划、目标等级概况和不断演变的等级概况的可视化，使运营商能够以高精度、更高的生产率和安全性实现目标等级。这一颠覆性的创新是使用廉价的基于计算机视觉的跟踪：1)在本地坐标系中跟踪挖掘机铲斗的位置；以及2)在同一坐标系中跟踪机舱安装摄像头的位置，以在增强现实中可视化掩埋的实用位置。广泛的现场测试表明，该技术跟踪相对于相机的标记，不确定度小于1英寸，与当前基于全球定位系统的方法相比具有显著优势，这些方法昂贵且对所追求的应用不可靠。