CPS: Synergy: Autonomous Vision-based Construction Progress Monitoring and Activity Analysis for Building and Infrastructure Projects

CPS：协同：建筑和基础设施项目基于自主视觉的施工进度监控和活动分析

• 批准号: 1446765
• 负责人: Mani Golparvar-Fard
• 金额: $ 99.99万
• 依托单位: University of Illinois at Urbana-Champaign
• 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 2019-12-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1446765&HistoricalAwards=false
• 关键词: CPS; Synergy; Autonomous; Vision; based

This Cyber-Physical Systems (CPS) award supports research to enable the automated monitoring of building and infrastructure construction projects. The purpose of construction monitoring is to provide developers, contractors, subcontractors, and tradesmen with the information they need to easily and quickly make project control decisions. These decisions have a direct impact on the overall efficiency of a construction project. Given that construction is a $800 billion industry, gains in efficiency could lead to enormous cost savings, benefiting both the U.S. economy and society. In particular, both construction cost and delivery time could be significantly reduced by automated tools to assess progress towards completion (progress monitoring) and how construction resources are being utilized (activity monitoring). These tools will be provided by advances in the disciplines of computer vision, robotics, and construction management. The interdisciplinary nature of this project will create synergy among these disciplines and will positively influence engineering education. Partnerships with industry will also ensure that these advances have a positive impact on construction practice.The process of construction monitoring involves data collection, analysis, and reporting. Research will address the existing scientific challenges to automating these three activities. Data collection will be automated by recording video with aerial robots and a network of cameras. Key research objectives are to derive planning algorithms that guarantee complete coverage of a construction site and to derive vision-based control algorithms that enable robust placement and retrieval of cameras. Analysis will be automated with a digital building information model with respect to which construction resources can be tracked. Key research objectives are to improve the efficiency and reliability of image-based reconstruction, to recognize material properties as well as geometry, to establish a formal language for representing construction activities, and to extend a parts-based approach for automated activity recognition. Reporting will be automated with a ubiquitous display of the digital building information model. Key research objectives are to formalize a constraint construction ontology with associated classification mechanisms and allow for systematic earned value analysis of construction progress. Experimental validation will focus on monitoring construction of substructure and superstructure skeletal elements in buildings and infrastructure systems as well as the associated earth-moving, concrete placement, and steel erection activities that are common in construction projects.

该网络物理系统 (CPS) 奖项支持对建筑和基础设施建设项目进行自动监控的研究。施工监控的目的是为开发商、承包商、分包商和商人提供他们所需的信息，以便轻松快速地做出项目控制决策。这些决策直接影响建设项目的整体效率。鉴于建筑业是一个价值 8000 亿美元的行业，效率的提高可能会带来巨大的成本节约，从而使美国经济和社会受益。特别是，通过自动化工具评估完工进度（进度监控）以及施工资源的利用方式（活动监控），可以显着减少施工成本和交付时间。这些工具将由计算机视觉、机器人技术和施工管理学科的进步提供。该项目的跨学科性质将在这些学科之间产生协同效应，并对工程教育产生积极影响。与行业的合作也将确保这些进步对施工实践产生积极影响。施工监测过程涉及数据收集、分析和报告。研究将解决这三项活动自动化所面临的现有科学挑战。通过使用空中机器人和摄像机网络录制视频，数据收集将实现自动化。主要研究目标是导出保证建筑工地完全覆盖的规划算法，并导出基于视觉的控制算法以实现摄像机的稳健放置和检索。分析将通过数字建筑信息模型实现自动化，可以跟踪建筑资源。主要研究目标是提高基于图像的重建的效率和可靠性，识别材料属性和几何形状，建立表示施工活动的形式语言，并扩展基于零件的自动活动识别方法。报告将通过数字建筑信息模型的无处不在的显示实现自动化。主要研究目标是通过相关的分类机制形式化约束构建本体，并允许对构建进度进行系统的挣值分析。实验验证将侧重于监测建筑物和基础设施系统中的下部结构和上部结构骨架元件的施工，以及建筑项目中常见的相关土方移动、混凝土浇筑和钢筋安装活动。