CAREER: Hybrid 3D Unstructured Workspace Modeling: A Critical Component in Developing an Automated Construction Site

职业：混合 3D 非结构化工作空间建模：开发自动化施工现场的关键组件

• 批准号: 1055788
• 负责人: Yong Cho
• 金额: $ 40万
• 依托单位: University of Nebraska-Lincoln
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2011
• 资助国家: 美国
• 起止时间: 2011-07-01 至 2013-09-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1055788&HistoricalAwards=false
• 关键词: CAREER; Hybrid; 3D; Unstructured; Workspace

The objective of this Faculty Early Career Development (CAREER) program award is to create an innovative 3D workspace visualization method, which will enable automated construction equipment to safely and efficiently handle construction materials for robotic field erection and connection. Robotic construction material handling requires both rapid visualization of the workspace and highly accurate position data for safe and secure physical contact between a target object and a robot. These are difficult to achieve with current sensor technologies. To meet this challenge, a target-focused range data collection and modeling method will be researched through a hybrid approach that integrates a light-weight 3D laser scanner with secondary and tertiary sensory devices such as a laser rangefinder and an infrared camera. A hybrid system mountable on a robot or piece of equipment will significantly reduce data collection time while enhancing data accuracy. Automatic target detection and model-based fitting and matching algorithms will be developed for various shapes of construction material components. The hybrid approach will be tested using real-world robotic test beds, including a multi-joint arm robot at the University of Nebraska-Lincoln and a bolting robot and a robot crane located within Korea University's automated building construction system. If successful, the results of this research will enhance the development of more intelligent and automated construction job sites and manufacturing processes by providing a fully sensed, monitored environment for materials, equipment, and operators. This research will also positively impact the environment by reducing the enormous amount of construction waste, which will greatly benefit the construction industry and society in general. Finally, this project has strong educational plans that will nurture tomorrow's leaders in engineering and science, promote lifelong learning for industrial practitioners, and broaden participation of underrepresented groups in research.

这个教师早期职业发展（职业）计划奖的目的是创建一种创新的3D工作区可视化方法，该方法将使自动化的建筑设备能够安全有效地处理机器人现场勃起和连接的建筑材料。机器人的建筑材料处理需要快速可视化工作空间和高度准确的位置数据，以确保目标对象和机器人之间的安全性接触。当前的传感器技术很难实现这些目标。为了应对这一挑战，将通过混合方法研究以目标范围的数据收集和建模方法，该方法将轻量重量的3D激光扫描仪与二级和第三级感觉设备（例如激光测距仪和红外摄像机）相结合。可以在机器人或设备上安装的混合系统将大大减少数据收集时间，同时提高数据准确性。自动目标检测和基于模型的拟合和匹配算法将针对各种建筑材料组件的各种形状开发。混合方法将使用现实世界的机器人测试床进行测试，包括内布拉斯加州林肯大学的多关节手臂机器人，以及位于韩国大学自动化建筑建筑系统内的螺栓机器人和机器人起重机。如果成功的话，这项研究的结果将通过为材料，设备和操作员提供完全感知的，受监控的环境来增强更智能和自动化的建筑工作地点和制造过程的开发。这项研究还将通过减少大量的建筑浪费来对环境产生积极影响，这将极大地使建筑业和社会受益。最后，该项目制定了强大的教育计划，可以培养明天的工程和科学领导者，促进工业从业人员的终身学习，并扩大代表性不足的研究团体的参与。