Realt-Time Spatial Information Acquisition and Use for Infrastructure Construction and Maintenance

实时空间信息获取和用于基础设施建设和维护

• 批准号: 0409326
• 负责人: Carlos Caldas
• 金额: --
• 依托单位: University of Texas at Austin
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2004
• 资助国家: 美国
• 起止时间: 2004-09-01 至 2008-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0409326&HistoricalAwards=false
• 关键词: Realt; Time; Spatial; Information; Acquisition

CMS-0409326: Real-Time Spatial Information Acquisition and Use for Infrastructure Construction and MaintenanceABSTRACTCurrent methods for spatial information acquisition and modeling rely on expensive laser range scanners that produce dense point clouds which require hours or days of post-processing to arrive at a finished model. While these methods produce very detailed 3D models of the scanned scene, the associated computational time burden precludes these methods from being used onsite for real-time decision-making. A rapid modeling approach for modeling local scenes for construction equipment operations, developed by the investigators with previous NSF support, presents significant advantages over full range scanning that require computationally intensive image processing. This approach provided a foundation for the development of the proposed novel methods of acquiring, integrating, modeling, and analyzing project site spatial data, including dynamic site information (motion of personnel and equipment), that allow scalability and robustness for real-time field deployment. These methods will enable complete local area modeling in the order of seconds, and with sufficient accuracy for applications such as real-time safety monitoring and advanced equipment control. The development of a real-time obstacle avoidance system using rapidly generated site models is also proposed, as well as an experimental plan with real infrastructure operation sites and equipment, to validate the proposed site data acquisition and obstacle avoidance methods. It is expected that the proposed approach will result in significant equipment safety improvements while at the same time lessening the need for skilled workers to operate heavy equipment in a wide range of site working conditions. Initial experimental work has demonstrated the feasibility of this approach.The construction industry accounts for a large percentage of workforce fatalities in the United States. An Occupational Safety and Health Administration (OSHA) study of on-the-job fatalities in the construction industry in the U.S. has shown that over 50% of the accidents stemmed largely from operation of heavy equipment. One of the major causes of these accidents is the lack of safety features installed on heavy equipment that is currently in use. Great potential exists in making heavy equipment safer and more efficient by developing a system that would integrate effective acquisition and handling of externally sensed site spatial information in real-time. With the internal sensors and computing power available commercially now to retrofit equipment, such systems are technically and economically feasible. The aim of the proposed research is therefore to develop methods and technologies that would allow an operator to operate equipment more safely and at higher speeds in cluttered environments, even in situations where visibility is poor as in underground work. The technologies proposed by the research team would assist in minimizing the impact of key types of human error and will have the potential to radically improve safety and efficiency of infrastructure operations that involve heavy equipment.

CMS-0409326：实时空间信息获取和用于基础设施建设和维护摘要当前的空间信息获取和建模方法依赖于昂贵的激光测距扫描仪，该扫描仪产生密集的点云，这些点云需要数小时或数天的后处理才能得到最终的模型。 虽然这些方法产生非常详细的扫描场景的3D模型，但相关的计算时间负担使这些方法无法在现场用于实时决策。一种快速建模方法，用于建模建筑设备操作的局部场景，由调查人员在以前的NSF支持下开发，与需要计算密集型图像处理的全范围扫描相比具有显着优势。这种方法提供了一个基础，提出的新方法的开发，采集，集成，建模和分析项目现场空间数据，包括动态的网站信息（人员和设备的运动），允许可扩展性和鲁棒性的实时现场部署。这些方法将能够在几秒钟内完成完整的局部区域建模，并具有足够的精度，适用于实时安全监控和先进设备控制等应用。还提出了一个实时避障系统的发展，使用快速生成的网站模型，以及实验计划与真实的基础设施的操作网站和设备，以验证所提出的网站数据采集和避障方法。预计拟议的方法将大大改善设备安全，同时减少对熟练工人在各种现场工作条件下操作重型设备的需求。初步的实验工作已经证明了这种方法的可行性。在美国，建筑业占劳动力死亡人数的很大比例。职业安全与健康管理局（OSHA）对美国建筑业工作死亡的研究表明，超过50%的事故主要源于重型设备的操作。这些事故的主要原因之一是目前使用的重型设备缺乏安全装置。通过开发一个系统，将有效地获取和处理外部感测的现场空间信息的实时集成，在使重型设备更安全和更有效方面存在着巨大的潜力。 随着内部传感器和计算能力现在商业上可用于改造设备，这样的系统在技术上和经济上都是可行的。因此，拟议研究的目的是开发方法和技术，使操作员能够在混乱的环境中更安全地以更高的速度操作设备，即使在地下工作中能见度很差的情况下也是如此。研究小组提出的技术将有助于最大限度地减少关键类型的人为错误的影响，并有可能从根本上提高涉及重型设备的基础设施运营的安全性和效率。